Author: Filipa Perdigão

AI automation platform
Articles

Choosing an AI Automation Platform for your Contact Center

Selecting an AI automation platform to streamline your Contact Center interactions is not a decision to be taken lightly. In this article, we will tell you what questions you should ask and how to choose the one that best suits your needs.

What is an Automation Platform?

Well, an automation platform is a technological solution that allows you to optimize processes by automatically handling repetitive and tedious tasks which do not necessarily require human intervention.

There are numerous platforms for automating various services. However, in this article, we will focus on the Contact Center, which is associated with conversational systems, such as chatbots.

Chatbots are conversational robots. In other words, they are systems that are programmed and designed to have human-like conversations. The goal is for interactions to be as natural as those exchanged with a real person.

The chatbots are the end product of the platform to be implemented, and it’s on that same platform where you will customize and maintain them.

It’s important to understand that there are two types of platforms: those that have AI and those that do not – and that AI makes all the difference.

What is Artificial Intelligence?

AI or Artificial Intelligence is a vast technological field of computer science that enables robots to behave identically to humans. In the case of chatbots, AI allows them to understand what people say and learn from those interactions.

For these kinds of conversational systems, the most important areas of Artificial Intelligence are Natural Language Processing (NLP) and Machine Learning.

Associated with computational linguistics, NLP, or Natural Language Processing, is the branch that allows the chatbot to process and understand human language, both written and spoken.

Click here to learn more about NLP chatbots.

Machine Learning, on the other hand, is the branch that enables the chatbot to learn from the different interactions it has with its users.

With these two forms of input combined with previously programmed learning models, the AI-powered robot is able to answer a variety of complex questions, even if they aren’t yet programmed in its knowledge base.

To learn more about Machine Learning in chatbots, click here!

Why Choose an AI Automation Platform?

If you think that an automation platform without AI can solve all your problems, think again.

Although they’re useful to a certain extent, interactions with these solutions are based on decision trees where the users click buttons until they get to the desired answer. With such a rigid structure, they may not get what they’re looking for. When they ask a specific question, the chatbot can’t respond.

In contrast, an AI automation platform can answer users’ spontaneous questions. In this way, it makes services much faster and more efficient.

How to Choose an AI Automation Platform?

Before choosing the AI automation platform provider, reflect on your needs with these questions.

1) What sectors do you usually work with?

It’s important that the provider has experience and expertise in the industry in which your Contact Center operates. All of your accumulated know-how should be efficiently utilized to accelerate implementation and bring more intelligence to the chatbot from the start. Terminology, types of questions, workflows, and queries are very different when we talk about health, retail, education, banking, or insurance.

Of course, these platforms are customizable, but it’s better to choose one that already has a long history in your area. Check out the use cases, success stories, references, and previous implementations before you make a decision.

2) Is the technology user-friendly?

Your contact center staff already has to familiarize themselves with all kinds of information about your products and services to effectively help customers.

It’s counterproductive to make them learn complicated programming and data science, the idea is to reduce stress with an AI automation platform.

Choose platforms developed with non-technical people in mind, which are intuitive and easy to use.

The whole point is to optimize your team’s work. Choose bots that adapt to you, not the other way around!

3) Is it simple to integrate with the systems my company uses?

Obviously, you already have your CRM systems to manage and analyze your customer interactions and data.

That said, two things are essential to know. The first is whether it’s possible to integrate the new platform with the programs you already use daily, and the second is whether this integration is easy to do.

Many companies will tell you that they integrate with all kinds of systems. However, this integration can be time-consuming and complex, and the time to launch the solution into your services may be unrealistic and, surprise, gets delayed.

Be careful to choose a vendor who is prepared to deliver a platform with an efficient and transparent strategy to minimize onboarding time without worry.

4) How scalable is the technology you’re going to invest in?

The technological world is constantly growing and won’t wait for the unsavvy.

Be sure that the AI automation platform you invest in keeps up with new trends and the company that provides it is continually improving it with new updates and features to give you the best possible experience every time.

5) Can they ensure the security and protection of my company’s and my customers’ data?

Adopting any technological solution has its risks, and more and more customers and companies prioritize the security and protection of their data.

Data security and protection are significant factors, as we are talking about confidential and personal data. It must be assessed in detail and ensure compliance with laws, such as the GDPR.

Ask what security measures each provider has in place on their platform. Find out what defense mechanisms they use, how often systems are audited, and whether all employees are informed of these same levels of security.

6) What kind of relationship would we have?

To work and to last, the relationship with the supplier must be close and committed. A true win-win partnership. Don’t just look for a company that provides you with a platform and then leaves you to figure out its specifics on your own.

The ideal vendor would provide training and coaching every step of the way, from configuration to customization, implementation, evolution, maintenance, etc., and who understands that the success of one is the success of the other.

Give preference to a company that offers you a proactive, personalized, and quality service. That when you ask questions, you know they will answer them promptly and address any concerns. And that when you have suggestions for improvements or specific needs, you can always count on their support.

From Theory to Practice

At Visor.ai, we are well aware of the challenges that contact centers of large companies, such as banks and insurance companies, face, which is why we strive to offer the best possible AI automation platform.

Through an attractive and intuitive design, everyone who uses it can autonomously edit and update whenever they want.

With an automation level of up to 80%, your contact center teams can finally focus on handling more complex requests that demand a higher level of attention.

In addition, it’s a fully cloud-based platform, which allows, with appropriate security measures, your employees to access it from home if they are working remotely.

And since it’s scalable, it can be implemented on communication channels such as the website, Facebook, or WhatsApp. You can even automate your emails through the email bot solution.

With Visor.ai, you will never feel helpless or unsure of what direction to take because our team will always be there to help you move forward.

Seeing is believing: we will gladly show you our AI Automation Platform in action!

Click here and request a demo

Speech Recognition (Reconhecimento da Fala)
Articles

Speech Recognition: How You Can Talk to Your Chatbot

The ability to audio communicate with a chatbot is due to a technology called Speech Recognition, and this is what we will talk about in this article.

If you were curious and want to know how this feature benefits chatbots, read on!

 

What is Speech Recognition?

There was a time when having robots help you with certain tasks was just something out of a movie. Yet, faster than we thought, chatbots appeared. And after a while, those same chatbots evolved and started talking to us and us with them.

Speech Recognition is a branch of Computer Science and Computational Linguistics. It’s a field that develops methodologies that allow computers to translate speech inputs into written text.

In addition to Speech Recognition, this technology is also known as Speech Recognition, ASR (Automatic Speech Recognition), Computer Speech Recognition, or Speech to Text (STT).

 

How does Speech Recognition work?

As the name implies, this technology allows recognizing the user’s voice commands and their conversion into text to be processed by the system.

 

There are two types of Speech Recognition:

1. Speaker-dependent

These are speech recognition systems that require training. In this training, a speaker reads texts or just loose vocabulary to feed the computer’s knowledge base.

This type of Voice Recognition is more accurate since it analyzes the person’s voice in question and tunes the system to recognize that particular voice.

 

2. Speaker-independent

On the other hand, these speech recognition systems do not require training. They do not recognize specific voices but analyze and translate into text what has been said.

An example of the use of this software occurs in telephone applications.

 

The Correlation between Speech Recognition and Artificial Intelligence

Artificial Intelligence or AI is the science that enables a machine to perform tasks, once performed by humans, and to mimic their reasoning process. In other words, it provides, so to speak, some level of intelligence to a system.

AI is currently used in many different areas, and depending on the technologies implemented, the software can perform certain actions.

Sometimes confused, AI and Machine Learning (ML) are distinct yet related concepts. Simply put, Machine Learning is a branch of Artificial Intelligence and is the technology that allows a machine to learn without the need for human intervention.

For a system to learn, it needs to be fed large volumes of data to recognize patterns and thus characterize them.

Speech Recognition and AI are intertwined by learning processes and data processing.

As we mentioned earlier, Speech Recognition software needs large volumes of inputs to provide the best possible performance. That’s where AI comes in with the automation of these processes.

In addition, there is also NLP (Natural Language Processing), another branch of AI, which enables the processing of human languages. For example, English, Portuguese, Spanish, etc.

 

Chatbots vs. Voice bots

Chatbots are possibly one of the most accessible ways to see Artificial Intelligence in action.

These conversational agents use areas of AI, namely ML and NLP, to communicate with humans.

Through these technologies, they can understand and extract the information given to them by written messages and respond.

Chatbots are service automation solutions often found in various digital communication channels, such as company websites, WhatsApp, Facebook Messenger, etc.

Learn here how digital channels can transform your communication with your customers!

On the other hand, there are voice bots, or, more often known as virtual assistants.

These, just like chatbots, have the goal of automating certain processes but with a more personal role.

They work as a kind of personal assistant that responds to voice inputs. The most common examples are Siri and Alexa. But every day, more companies launch their own voice bots.

So, to summarize, companies mostly use chatbots to automate their services (internal or customer support), and their inputs and outputs are written messages. As the name might suggest, voice bots only receive voice commands and respond in the same way. Moreover, they have a more individual support role.

 

Speech Recognition: The Ears of Your Chatbot

Knowing the difference between chatbots and voice bots, it’s also possible to add a third option involving both solutions – speech recognition chatbots or voice chatbots.

As we mentioned earlier, Speech Recognition technology is what allows a system to convert voice commands and translate them into text.

Once translated, that information goes through the same processing that a written text message would have in a “normal” chatbot.

Just like giving OCR the ability to read the text contained in images, you can also give your chatbot the ability to listen.

If you were curious about what OCR is, you might be interested in the following article: OCR: Give Eyes to Your Chatbot.

 

The Benefits of Speech Recognition Chatbots

Users are becoming more and more interested and demanding regarding these technological solutions.

If it’s to be as similar to human dialogues, then both chatbots and voice chatbots have to meet the demands and characteristics of those same conversations.

Eliminating waiting time, and getting answers that correctly answer our questions are two examples of what your customers expect. Be it by message or by voice.

Nobody likes to be talking and get an answer that has nothing to do with the topic. In such cases, you might as well send the user to human assistants via Live Chat.

Learn more about the advantages of having a chatbot and Live Chat here!

 

A chatbot already brings many advantages to your company, such as:

  • 24/7 service
  • Decreased response time
  • Automation of repetitive processes
  • A way of capturing commercial leads
  • Increased satisfaction of customers and their teams
  • Means of supporting customers and/or employees

Still, between writing and speaking, no doubt speaking is much more natural for a human being. For this reason, the inclusion of voice commands takes your chatbot to another level.

 

A voice chatbot gives you the following benefits:

1) Provides more “human-like” interactions

As we already mentioned, speech is much more natural than writing. For this reason, you get communications that are more spontaneous and not as thought out, as is the case with written messages.

This spontaneity is very useful for your chatbot, as it increases its knowledge base and improves its AI with the various commands it receives.

 
2) Improves user experience

Companies are very concerned about the usability and user experience on their website and communication channels.

If a chatbot already greatly improved the user experience when navigating to your website, having the ability to talk to the chatbot improves it even more.

 
3) Enables multitasking

Also related to the consumer experience, the voice option allows the consumer to do other tasks while asking your chatbot for information.

This factor, as well as the others, greatly increases customer satisfaction in that they don’t have to stop doing what they are doing to communicate with the bot.

 
4) More inclusive solution

Despite being an almost non-existent factor (thankfully!), there are still illiterate people who, for some reason, have not learned to write.

Other than that, there are people with motor disabilities that can’t use keyboards or other types of tactile devices.

Voice can be the ideal solution to include and show that all your customers are taken into consideration.

 

Visor.ai Voice Chatbots

Visor.ai chatbots are a great option to enhance your Customer Support or internal employee support services.

Our solutions rely on in-house developed NLP and Machine Learning to meet our requirements and our customers’ needs.

This way, we make sure that our customers get the results they want and, if changes are needed, we don’t have to rely on third parties.

Besides being quick-to-implement solutions, they’re easily adaptable with any integration the customer wants, including voice functionality.

Learn more about how to include these spectacular solutions in your digital communication channels… Let’s Talk!

If you are interested in this topic, we also suggest you download these ebooks:

rpa chatbots
Articles

RPA and Chatbots: The Most Incredible Combination

Because they are related to automation, people may think that RPA and chatbots are the same thing, but they are not. In this article, we clear up all the doubts about what they are, what each one does, their differences, and some use cases.

Automation with Artificial Intelligence

Humans have long tried to find ways to automate repetitive processes that become monotonous.

More than ever, process automation is crucial to the evolution of industries.

Utilities, manufacturing, energy, finance, healthcare, and most industries have already adopted some form of automation, and it is towards a more automated world that we are moving.

An area closely associated with automation is Artificial Intelligence (AI). This gives machines the ability to perform tasks that humans once performed. In addition, it allows us to simulate some of our reasoning.

What is RPA?

RPA stands for Robotic Process Automation. It’s an Artificial Intelligence technology that, as the name implies, uses software robots to automate certain tasks.

RPA is one of the most popular AI tools, as it allows companies with older systems to optimize workflows and reduce costs.

How do RPAs work?

As we already mentioned, RPA robots take charge of repetitive digital tasks, such as filling out forms or copying and pasting information. To do this, these robots access information from your IT systems.

RPA solutions can be of three types:

  • Attended RPA: is an assisted automation, where the robot works under supervision.
  • Unattended RPA: is independent automation. That is, it does not require human intervention. However, it is controlled by other software systems.
  • Hybrid RPA: is a combination of the two previous types.

Regarding the tasks that each type of RPA performs, the first case is used to complement human tasks, and the second is more used for tasks that involve repetition and large volumes of data.

Which is the best option for you?

Well, that will depend on the actions you want to automate in your company.

If they are to support your employees, assisted RPA is probably the best option.

If you want to automate large volumes of information, unattended RPA is the solution.

And Chatbots? What are they?

You already know what RPAs are, now is chatbots’ turn.

Chatbots are conversational robots, also known as AI bots, conversational AI, or virtual agents. They are chat systems generally used in companies to automate and optimize their Customer Care services.

They are systems that also use Artificial Intelligence, recognizing the requests made by users and giving them an answer.

When the questions are more complex, they forward the customer to Live Chat, where the customer is assisted by a human assistant who helps him solve the problem.

Find out here which is the best option for your company: Live Chat or Chatbots!

What are the Differences between Chatbots and RPA?

Although chatbots and RPAs are automation solutions, they are quite different.

One of the differences that stands out the most is that chatbots can communicate with a person, while RPAs are not.

RPAs, unlike virtual agents, do not have any language recognition technology associated with them, so it is not possible to communicate with them.

Therefore, as we have already mentioned, they are ideal for back-office tasks that do not involve interactions with third parties.

Confronting one solution with the other, we can see the following differences:

RPA

  • No linguistic knowledge
  • The goal is to automate processes
  • Focused on back-office processes
  • Receives structured information
  • Supports IT teams

Chatbots

  • Has linguistic knowledge
  • The goal is to automate conversational processes
  • Focused on clarifying user doubts
  • Receives different forms of information
  • Support for business teams

Why Implement RPA and Chatbots in your Company?

Now that you know what RPA and chatbots are and their differences let’s see what you gain by having these two automation solutions. And how, together, they can be an asset to your company.

8 Advantages of RPA Solutions

Speed and Consistency

People once carried out the processes that are currently performed by these bots.

They usually involve large volumes of information, and to have reliable results, high levels of attention are required. In other words, the degree of error due to human failure can also be high, as can the time it takes to process the data.

However, RPA technology allows these procedures to be performed quickly and with low error levels since a bot can perform the same task over and over again without going off schedule.

Cost-effective

Besides being fast to perform repetitive tasks, they are cost-effective solutions.

Since there are no failures, there is no need to repeat procedures. So you save money. And even if you have to start from scratch, it’s much faster and again saves resources.

Increased Productivity of your Employees

As we have already mentioned, RPA enables the automation of repetitive and monotonous processes that were once performed manually.

Without the need to occupy your workers with these procedures, you have a freer and more focused team on more complex and less repetitive processes.

In this way, your team’s performance level increases.

Increased Customer Satisfaction

Although RPA solutions are implemented for back-office tasks, they also have an impact on your customer satisfaction levels, since they allow you to offer a higher quality service.

Therefore, in direct relation, you have more satisfied customers who will certainly be loyal to you.

Versatility and Connection between several Systems

RPA technology is very versatile, as it can be implemented and have various applications depending on the industry.

For example, in the financial sector, it can automate information validations, create reports for customers, form filling, among others.

Another example, in the retail industry, you can automate the extraction of product information or automatically update the inventory on your website.

Improved IT management and support

Because RPA improves the operational quality of the back office and monitors your network, it allows you to deal with potential problems in less time and therefore without requiring extraordinary resources.

What your Company Needs is a Chatbot with RPA!

The benefits of RPA and chatbots are very similar. However, and as we have already pointed out in the section on the differences between the two solutions, chatbots have the ability to understand and communicate with their users.

Still, it’s possible to merge the two solutions and create RPA Chatbots.

RPA Chatbots combine the processes automation of RPA and the communication capabilities of chatbots with Artificial Intelligence.

For example, while the chatbot talks to your customers, the RPA bots gather information from external systems. This way, you can offer an even more complete service without overloading your employees.

Moreover, if you have an internal chatbot to support your employees, you don’t need your staff to learn how to work with different platforms.

Just provide them with a chatbot in which they ask for information, and the RPA bots linked with your chatbot will gather that same data.

Furthermore, users can, for example, request updates from CRM systems, among others.

This saves time and makes your team’s work more efficient!

Want to enjoy the benefits of automating your processes and communications?

Talk to us!

Articles

How Can Chatbots Boost Your Digital Transformation

As the world becomes more digital, businesses must keep up with this evolution and adapt to new technologies. To do this, various industries need to invest in digital transformation. And one simple way to drive this transformation is through chatbots.

Keep reading this article to learn more about digital transformation, how a chatbot can be a great tool to improve your services and increase your customers’ satisfaction and experience.

What is Digital Transformation?

Surely, you have heard of digital transformation.

This concept is related to companies that want to reach further and stand out from the competition.

The world is a place where communication and globalization are increasingly emphasized while at the same time making a certain topic known.

But what exactly is digital transformation? – you ask.

Well, digital transformation, as the name might imply, is the adaptation of an entity (company) to new technological trends, thus becoming more digital and innovative.

The integration of new technologies totally changes the way products/services are offered to consumers, which they highly value.

Users are more demanding and losing interest in companies that do not keep up with the times.

The updating and investment in innovative solutions are fundamental to have global satisfaction, both from customers and employees.

Which areas should you transform digitally?

Digital transformation cannot occur in just a certain part of a company.

Have you seen what it would be like if half your employees benefited from the perks of new technology and half didn’t? Or that customer service was all revamped, but on the other hand, you had your employees in less advantageous situations?

That wouldn’t be good, right? Then the answer is simple. Do a general upgrade, even if it’s in phases. But don’t leave anyone out.

Internally

As we have already mentioned, you must make your employees happy in addition to your customers.

Improving the quality of work of your employees is crucial. So invest in solutions that improve their performance. Namely, machines that perform the most physically demanding tasks, for example.

In retail companies, for example, try to upgrade the production lines for your products.

Externally (Customer Support)

Your customers expect you to always be on top of the latest trends, both in products and service.

No one has time to wait around anymore. People want to be attended to immediately. And if not, they will turn to other solutions.

Besides, if they can solve their problems themselves, without having to talk to someone else, all the better.

Self-service is a trend that will not disappear any time soon, and any service will use it.

Digital Transformation with Artificial Intelligence

Today, any company that wants to offer a higher level of service turns to Artificial Intelligence.

Artificial Intelligence is the field of Computer Science that enables machines to simulate reasoning and perform human activities.

According to Andrew Ng, AI is the new electricity. By this, the computer scientist and professor at Stanford means that it’s as important to the present day as electricity was when it was discovered.

It’s a matter the world can no longer live without and is indispensable to its progress and evolution.

Let’s look at examples of different uses of AI today:

Online shopping and advertising

Strategies with AI used in retail are exciting, as they allow brands to offer a more personalized service to each customer.

Web Searches

It’s already known that only the best blog posts/articles appear in the first positions in search engines. But how do we know which are the best?

This work is done by AI bots that automatically check all sites to deliver the best results.

AI can be a good strategy when the topic is SEO (your website’s performance in search engines). Learn more here!

Automatic Translations

It may be one of the most used services in the world. Instantly, it has the translation from one language to another, with a very high degree of correctness.

At first, programs like Google Translate had their limitations and were not very efficient. But as their knowledge bases grow and they have a greater volume of data to analyze, they become more and more correct.

NLP is a technology used for machine translations. Learn more about this branch of AI here!

Cyber Security

AI-powered systems can help recognize and counter threats to systems by recognizing patterns and mapping attacks.

Combating Misinformation

Just like the previous point, to combat disinformation, we can use AI. That is, nowadays, anything can go viral. This can be great for spreading information, except when it’s incorrect and baseless.

The role of Artificial Intelligence, in this regard, is to prevent and combat false information from spreading.

In a way, this use of AI was driven by the coronavirus pandemic, where anyone had their theories about the cure and prevention methods.

Virtual Agents

Probably the best-known use is virtual agents or chatbots.

These systems are process optimization and automation solutions that are more and more implemented in companies with large contact volumes.

Digital Transformation with Chatbots

Chatbots, being virtual agents, help optimize your company’s services, both internally and with the customer.

The implementation of more digital solutions enhances growth and increases the satisfaction of your customers and employees.

1) Customer Service

Investing in automation solutions such as chatbots is a key step if you want your institution to stand out from the rest, especially in customer service.

One of the most frequent complaints from consumers is the time they wait to be attended to.

So, if the waiting time is a factor to be taken into account and you suffer from this problem, maybe investing in a chatbot is not unreasonable.

Instead of keeping the user waiting, let them deal with their problems by themselves, and only if they can’t solve them, refer them to a human assistant.

Many of the questions received by contact centers are repetitive and easy to solve. That said, there is nothing like a chatbot programmed and trained to answer your customers’ most frequently asked questions.

2) Sales Support

In addition to customer support, a chatbot can be an essential solution to help you in pre and post-sales.

In pre-sales, it can help educate your prospects about your brand or make suggestions for services and products that complement what they are purchasing.

On the other hand, it can be an option for problem-solving in the post-sale, such as complaints or other situations.

3) Lead Generation

A virtual agent is also a great marketing tool. Especially in the world we live in today, where social networks and digital channels are some of the biggest means of expansion and propagation of brands.

Implementing a chatbot on the digital channels your customers use the most or your persona is on is a great strategy to expand. And, at the same time, start creating a connection with your target audience.

For example, program your chatbot to greet and introduce your product to people who pass through your channels.

Learn about the benefits of adopting various digital communication channels here.

4) Collecting Analytics

One of the most interesting features of a chatbot is the metrics collection.

With these communicational agents, in addition to assisting your customers, they can gather information about them, namely demographic data, the product they are most interested in, etc.

5) Internal Relationship

Besides customer service, you can also implement a chatbot internally. That is, for employee support.

This implementation can increase the satisfaction level of your team and, simultaneously, create and maintain greater proximity between employees and the company.

Articles you might be interested in:

Visor.ai Helps You with Your Company’s Digital Transformation

Visor.ai offers solutions for chat and email automation. Both use Artificial Intelligence.

Visor.ai’s chatbots and email bots are easy and fast to implement. They come with a low-code platform, where you can customize and edit your bots autonomously.

Because they are cloud-based solutions, we can implement them remotely into the platforms you already use—namely, CRM systems such as Salesforce, etc.

Besides, Visor.ai follows all privacy policies, ensuring the security and privacy of your company’s and your users’ data. It also offers the possibility of VPC (Virtual Private Cloud).

To learn more about the VPC offer and its benefits, click here.

If your goal is to make your company more technologically advanced, talk to us and you will see how easy it is to stand out from the competition!

Let’s talk!

OCR in chatbots
Articles

OCR: Give Eyes to Your Chatbot

We live in a world where robots are increasingly common. There are chatbots on the company websites and machines that build cars and other equipment by themselves. More and more are the tasks that these agents can perform, and OCR is one of them.

This article tells you what OCR is, its applications, and how your company’s chatbots can use it.

What is OCR?

OCR stands for Optical Character Recognition.

It’s a technology widely used in Artificial Intelligence, Computer Vision, and pattern recognition.

As the name implies, this technology allows a machine to read the text in images and convert this information into code that the system understands.

The text can be printed, handwritten, or typed, and the conversion can be done from scanning or photography.

It can also, for example, read captions superimposed on an image, as is the case with movie subtitles.

The Origins of OCR

According to Schantz (1982), the first forms of OCR were related to telegraphs and reading devices for blind people.

To make such recognition possible, the first versions of this technology had to be trained with images of every character and every existing font.

In 1914, Emanuel Goldberg developed a machine that read characters and converted them into standard telegraphy code.

A few years later, entering the 1930s, Goldberg invented and patented the “Statistical Machine.” This used OCR code to search microfilm files. A while later, IBM bought that same patent.

The Applications of OCR by Sector

Today, OCR systems are already quite effective and capable of easily recognizing any text. That said, their use covers various sectors and purposes.

Banking sector

Reading and Extracting Information of checks – recognizes account number, written amount, and signature. Moreover, it’s used on procedures containing large volumes of documentation.

Insurance Sector

Like in banking, OCR can do information extraction on documents such as accident reports, collecting the cars involved in the claim, the signatures of the responsible parties, etc.

Retail Sector

You no longer have to carry around all the promotional stubs every time you go to the supermarket. Today, most supermarkets already have virtual receipts that can be scanned using OCR to extract the serial number.

Tourism Sector

These days, you hardly need to learn other languages anymore, because technologies take care of that for you. This is the case with automatic translations.

There are more and more applications where you point the camera of your smartphone at a label, for example, and you have all the information translated into your language.

These tools are also useful when traveling, and you want to read the indications on signs, such as geographical names.

Besides, you already see many automated systems at airports, where machines do the ticket verification without the need for human intervention.

OCR Technology in Chatbots

What are chatbots?

Chatbots (conversational robots) are virtual agents with Artificial Intelligence that automate communication processes. Companies widely use these types of bots in their services, such as Customer Support.

These agents need certain technologies, such as Machine Learning and Natural Language Processing, to understand and respond to us.

It may be interesting to consult the articles below to learn more about these technologies:

Furthermore, if you want your chatbot to perform other tasks, such as reading documents, you need to include OCR technology.

The Visor.ai OCR Use Cases

Visor.ai integrates, according to the customers’ needs and requirements, the OCR technology in its solutions.

Heineken Use Case

OCR can be an exciting capability for a chatbot to have, namely in marketing campaigns. Take the example of Heineken.

Heineken launched a campaign where consumers had to send a photo, via chatbot, as proof of purchase of their beers. After the receipt validation, the chatbot would award prizes to users.

You can read more about this case study here.

Email bots Use Case

Another automation solution that Visor.ai offers is email bots.

Email bots are solutions that automate processes that take place, in this case, in the emails that companies receive.

It’s an ideal solution for companies with high volumes of email contacts.

Besides reading the emails, categorizing, and forwarding them to the specialized service departments, these bots also read and check the documentation attached to the email.

That is, imagine you have an insurance company and a customer wants to report a car accident.

To do this, he/she needs to send, for example, the claim registration document and the identification document. However, the customer has only sent the claim document.

In this case, the bot reads the attachment and checks to see if the user properly filled out the documents. And, if the ID document is still missing, asks the user for it.

Only when it has all documents present and well filled out, the email bot passes the case to a human assistant.

Conclusions

OCR technology allows your chatbot or email bot to read and extract information from images/documents that have text.

With this capability, their complexity increases, and they become more efficient as they automate processes that take a lot of time away from their teams.

Whichever Visor.ai solution you’re interested in, talk to us, and we’ll be glad to look at the options that fit you best! Let’s talk!

If you are interested in this topic, we also suggest you download these ebooks:

vpc (virtual private cloud)
Articles

VPC: What It Is and What Are Its Benefits

If your company handles sensitive data and requires high levels of security, a Virtual Private Cloud (VPC) may be the right solution for you.

Learn what a VPC is, how you can implement it and what are its benefits.

What is the Cloud?

Starting at the beginning: what is the Cloud?

Like other terms that emerge in the technology industry, such as “Big Data” or “5G,” the term “cloud” by itself does not tell us much about its meaning.

Shortly, we use the term “cloud” to indicate that something is on the Internet rather than in a physical location. I.e., it’s anything that you can access remotely over the internet.

It can also be known as “cloud computing” or “cloud storage”.

When we say that something is in the cloud, it means that documents/information are on servers on the internet and not on your computer’s hard drive.

These servers are worldwide, so you don’t have to manage your own servers or run software applications.

People use the Cloud for its convenience and because it’s a reliable service. Besides, it’s widely used for:

  • Storing documents – you can access them through any device with an internet connection;
  • Sharing documents – makes it easy to share files with several people at the same time;
  • Backing up documents – some applications automatically copy your files to the cloud, so there’s no possibility of losing them if you lose access to your computer.

The differences between Public Cloud and Private Cloud

The cloud can have two parts: the public part and the private part.

The public cloud is a service that different customers share.

It’s called “public cloud” to distinguish from the general term “cloud” and includes services such as:

  • SaaS (Software as a Service) – a software distribution model. It’s a service where the cloud provider hosts applications and makes them available over the internet.
  • PaaS (Platform as a Service) – service that provides a platform for customers to develop, run, and manage enterprise applications without building and maintaining existing infrastructure in development processes.
  • IaaS (Infrastructure as a Service) – the provider manages IT infrastructures such as storage, server, and network resources and makes them available to customers over the Internet.

On the other hand, the private cloud is a service used by only one customer, i.e., it’s not shared with any other entity.

What is a Virtual Private Cloud (VPC)?

Picking up on previous concepts, a Virtual Private Cloud is a private cloud within a public cloud, as you can see in the image below.

This image shows a graphic with a Virtual Private Cloud within a Public Cloud.

With a VPC, you don’t share any computing services with other entities.

This isolation (within the public cloud) is possible due to the assignment of a private IP subnet and the construction of encrypted user communications.

VPC vs. VPN

As we have seen, a VPC is an isolated cloud within a public cloud. However, a VPC must be accompanied by a VPN.

A VPN or Virtual Private Network acts as a kind of lock. Only those who can pass the levels of authentication and encryption required on the VPN have remote access to the VPC.

In other words, a VPN creates a private encrypted network on a public network. This way, data from the VPN that passes through the public network is not visible to third parties since it’s encrypted.

Cloud Computing Providers

More and more companies are migrating their services to the cloud to accelerate their digital transformation. Moreover, it’s a fast way to empower remote work.

As a result, more and more companies are looking for providers that match the specific needs of each company.

According to the Gartner Magic Quadrant, the leaders in providing cloud services (IaaS) are Amazon Web Services, Microsoft Azure, and Google Cloud.

What Are the Benefits of Having a VPC?

Now that you know what a VPC is and what the principle providers are, it’s time to see what you gain by migrating and having your services on a Virtual Private Cloud.

1) Space Savings

By migrating your services to the cloud, you don’t have to worry about software management and upgrades. Also, you don’t have to worry about maintaining the servers on your premises.

2) High Security

As we mentioned earlier, only the authenticated user has access to the information present in the VPC.

Moreover, these service providers have every interest in keeping their clients satisfied, so they have high-security levels and review them regularly.

3) Easy Integration

A VPC can work in sync with other VPCs, a public cloud, or local infrastructures.

In these cases, when there is this synchronization of services, we called it a Hybrid Cloud.

By definition, a hybrid cloud combines public and private clouds along with a base infrastructure.

4) Seamless Updates

With users all on the same hardware, VPC’s distributor has an easier time performing upgrades with less downtime.

As providers acquire better hardware, the faster and more secure their customers’ workloads become.

5) Environmentally Friendly

Concern for the environment is a growing theme in society, and the business world is no different.

Companies are increasingly aware of their carbon footprint. And more conscious of the measures they need to take to become more sustainable and environmentally friendly.

With a VPC, you decrease your carbon footprint. As all the information is in the cloud, there is less consumption of material resources since you don’t need local dedicated hardware.

Visor.ai Solutions and VPCs

Visor.ai is a company that offers cloud-based solutions. That is solutions that are entirely in the cloud.

These solutions are modular, scalable, and easy to implement. And don’t require any human resources travel to integrate and use them.

Other than that, by working with the best cloud providers (AWS and Microsoft Azure), Visor.ai offers reliable and secure VPC solutions.

This way, companies that handle more sensitive data have the possibility to have a cloud that only they can access. This is the case of banks and insurance companies.

A VPC can be a great solution for companies that have extremely high levels of security.

If you are interested in Visor.ai’s automation solutions and think that a VPC is the best option for you, please contact us. We’ll be glad to talk to you!

Let’s talk!

NLP chatbots
Articles

What You Should Know about NLP Chatbots

If you are a person who is frequently out and about on the Internet, you have surely encountered chatbots on the websites of some companies. Perhaps you have even interacted with one. But have you ever wondered how they understand us? The answer is NLP.

Come and find out more about NLP in chatbots, what it does, and its applications!

Artificial Intelligence and Natural Language Processing

A machine does not have the same level of intelligence as a human (for now).

Nevertheless, it’s possible to make it do certain processes that the human brain and body perform. And for this, we use Artificial Intelligence.

There are two types of AI: “Embodied” AI and Software AI.

“Embodied” AI is so-called because it is integrated into more tangible, physical systems. That is robots, autonomous cars, drones, etc.

On the other hand, Software AI is associated with virtual agents, search engines, facial and speech recognition systems. Systems that do not have the physical component, like the previous case. Only exist in code.

What is NLP?

NLP or Natural Language Processing is a technology that is part of Software AI.

Its focus is to give machines the ability to understand written text and spoken words, just like a human being.

This branch of computational science combines Computational Linguistics (rule models of human language) with statistical models, Machine Learning (ML), and Deep Learning.

This combination enables machines to fully understand human language, including the intent and feeling expressed in utterances.

Discover what the role of Machine Learning is in AI chatbots.

But beware!

Please do not confuse it with NLP (Neuro-linguistic Programming). Despite having the same acronym and the area of Linguistics in common, they are distinct concepts.

While Natural Language Processing is associated with machines, Neuro-linguistic Programming is associated with humans.

It’s a pseudoscience that uses communicational, perceptual, and behavioral techniques that “reprogram” the human mind and thoughts to improve certain conditions, such as phobias or anxiety disorders.

The Differences Between NLP, NLU, and NLG

Aside from the confusion with Neuro-linguistic Programming, the same is also true of the concepts of NLU and NLG.

Very generally, NLU and NLG are components that belong to NLP.

According to IBM, NLU (Natural Language Understanding) is a subset of NLP that determines the meaning of an utterance (written or spoken) from the syntactic (grammatical structure) and semantic (intent) analysis of it.

On the other hand, NLG (Natural Language Generation), also a subset of NLP, enables the system to write. That is, it’s what enables the machine to respond in text in the human language. These texts can, through other systems, be converted into spoken speech.

7 NLP Applications and Use Cases

Now that you know what NLP is and how it differs from other concepts, it’s time to learn how we can apply this technology.

As we already mentioned and as the name implies, Natural Language Processing is the machine processing of human language, like English, Portuguese, French, etc. Therefore, its applications are directly related to language.

1) Speech Recognition

Also known as Speech-to-Text. This is the machine’s ability to convert spoken speech into written speech.

Every system that receives voice commands and responds in audio format uses this tech.

2) Text Summarization

As the name suggests, it’s the ability to summarize texts automatically.

It’s often used in larger texts, such as scientific articles or legal documentation, by extracting the most important information.

There are two types of Text Summarization:

  1. Extraction-based Summarization – the system summarizes by extracting the most relevant sentences from the text;
  2. Abstraction-based Summarization – the system paraphrases the predominant information from the text. This is the most common type and the one that works best.

3) Keyword Extraction or NER

As in the previous point, NLP can extract words that belong to a category type. For example, names, places, figures, etc.

You can also know this application by the acronym NER (Named Entity Recognition). It allows the recognition and categorization of certain words.

4) Intention Classification

In the same way that it’s possible to make a machine recognize words of a certain category, it’s also possible to make it recognize the implicit intentions in sentences.

For example, with the statement “If it weren’t so expensive…”, the system, with just this sentence, can understand what the user really meant: “if it weren’t so expensive, I would buy it.”

This NLP feature can help detect potential customers through your social networks, email, or chatbot.

Learn more about the Visor.ai email automation solution in Email Bots: How to Automate Your Email.

5) Spell Checking

Another very interesting NLP application is text correction.

There are more and more of these programs that support writers or editors when writing or revising text.

This NLP feature corrects spelling and grammatical errors and suggests the rephrasing of ungrammatical sentences.

6) Machine Translations

Using linguistic knowledge of several languages, a system converts one natural language into another. It retains the meaning of the input language and produces fluent speech in the output language.

One of the best-known examples of this feature is Google Translate. Although it had some problems initially, as its knowledge base grew and the field of neural networks evolved, it had great progress.

Machine translations are essential in the inclusive world we live in. The user is the center, and the wider the range of people we reach, the better.

7) Sentiment Analysis

It’s still somewhat difficult for machines to understand certain aspects, such as sarcasm or irony. Still, they can already tell whether it’s a positive or negative sentiment through certain clues or opinions.

NLP in Chatbots

Companies are increasingly using chatbots to streamline the work of their teams and automate Customer Services, providing a self-care service.

Yet, to communicate fluidly and efficiently, they need Artificial Intelligence, namely NLP and ML.

Natural Language Processing makes them understand what users are asking them and Machine Learning provides learning without human intervention.

These two technologies enable a conversation between a bot and a human similar to what two humans would have.

Still, some chatbots do not have these technologies associated. That is, without AI. As a result, they don’t have the ability to understand human language and communicate with users.

Features that Improve Your AI Chatbot

As we have already seen, NLP has numerous uses. However, in chatbots, we use features that enable greater speech fluidity.

On a general level, the most commonly used features in virtual agents are:

  • Speech Recognition

This tool is essential for chatbots that have a voice option. So whether it’s text or voice commands, your bot can recognize both inputs.

  • NER

NER is a great option for improving your system’s AI, as it increases the detail of your bot’s knowledge base.

  • Sentiment Analysis

Knowing another’s state of mind is a very human characteristic that allows us to react accordingly.

With sentiment analysis of user speech, your bot can also adapt, responding according to the attitude it receives.

For example, if a user is rude, the chatbot will have the capacity to recognize that interaction as negative.

  • Intent Classification

Like the previous features, intent classification allows you to increase your chatbot’s Artificial Intelligence performance.

This feature allows your virtual agent to understand intentions that are not expressed but are implied in user says.

Visor.ai Solutions

Visor.ai solutions are unique because our team developed both Natural Language Processing and Machine Learning in-house.

The decision to develop our own technologies and not use third-party solutions comes from the need to make our bots meet our expectations and our customers’ requirements.

Every day, we update and improve Visor.ai’s automation solutions always to offer the best services.

Do you want to learn more about our AI solutions? Don’t waste any more time and contact us!

partnerships in tech
Articles

How Important Are Partnerships in the Tech Industry?

Partnerships in the tech industry are essential.

Technology gets more complex every day, and it becomes impossible for a single company to keep up with all these developments. It is therefore essential for companies to come together to reach further.

Read on to find out what they are, what the different types of partnerships are, and how they can be successful!

What are Partnerships in Tech?

We humans always need other people, directly or indirectly, to achieve our goals and have good results.

From the very beginning of our lives, we’re dependent on each other to evolve. Be it in the very first seconds of life, when skin-to-skin contact is essential, or a little help when we take our first steps.

Whatever the stage, it’s fundamental that we have someone to lean on to go further.

The same happens in the business world. It’s always crucial to have other people and companies that complement us because, without these connections, we can move forward, but it will be a much longer path.

According to Investopedia, the definition of a “partnership” is an agreement between two or more entities to oversee and share business operations, as well as their earnings and responsibilities.

If we can all have gains, why not explore this option?

3 Steps to a Successful Partnership

As we have already mentioned, we must support each other. However, we have to know where we want to go, the goals we want to achieve, and the gains that a partnership will bring to both parties.

To have a successful partnership, you need to follow a few points, such as:

1) Define goals

The goals of the companies involved in the partnership must be well defined. The individual and the common objectives.

For example, one company may want to increase the number of customers and the other to find new ways to optimize its clients’ services. The common goal is to have satisfied and happy customers.

2) Sharing expectations and principles

It’s important that, as well as the goals, expectations are well-defined: those of each company and those of the clients.

Furthermore, as with interpersonal relationships, it’s necessary that the company with whom you partner has the same work principles and ethics as you do.

This may seem like an irrelevant issue. However, partnering with an institution that doesn’t follow the same standards can be very harmful, promoting disagreement and discussion.

So find a company that you identify with, both professionally and personally.

3) Keep communicating

Communicate, communicate, and communicate from the beginning to the end. Don’t let matters be left unsaid.

What may be obvious to you may not be obvious to others. It’s much easier to shape a relationship around stipulated points than to have to correct them later.

Communication is an issue that runs through all stages of a partnership. As we have already mentioned, when setting goals, discussing principles, etc.

Always be in touch with your partners.

4 Types of Tech Sector Partnerships

There are several types of partnerships in the tech industry, each with its own characteristics. At Visor.ai, we adopt four partnership models.

Referral Partnerships

Referral Partnerships are the partnerships of referral. That is, they’re partnerships for generating business opportunities.

In other words, imagine you have a client that wants a specific service, but your company can’t offer it. However, you know of another company that has this service and is your partner. You then tell your customer that you can provide the desired service but through another institution.

Integration Partnerships

The Integration Partnerships have to do, as the name implies, with the integration of systems with Visor.ai’s platform.

For example, Visor.ai is a company that offers a solution that needs integration with the customers’ systems and, when they are direct customers, it’s usually Visor.ai that does the integrations.

Nonetheless, in addition to referring customers, some partners also perform that part of implementing the solution.

Community Partnerships

On the other hand, there are specific partnerships to boost business growth.

They’re very much based on networking actions that allow reaching new customers, new partners, and mentors.

These Community Partnerships are key to helping smaller ones expand their contacts, thus reaching new funding opportunities and independent investors.

Technology Partnerships

Finally, technology partnerships deal with collaborations that involve software complementarity.

In other words, the joining of two or more technologies to achieve a goal and meet the clients’ needs and requirements.

Become a Visor.ai partner!

Visor.ai is a company in constant growth and development and offers automation solutions that adapt to any industry.

Besides being cloud-based, modular, and scalable, they’re completely adaptable to any system you use or that your customers use.

If you are interested in chatbots and/or email bot solutions with Artificial Intelligence or know any company, please feel free to contact us to form a successful partnership!

Join us!

chatbtos for seo
Articles

Chatbots: Are They the Unknown SEO Booster?

Many companies invest in chatbots to increase customer satisfaction and optimize the efficiency of their Customer Service. However, chatbots can also be a secret weapon to improve your website’s SEO.

Find out what SEO is and how chatbots can bring your website to the top of the search engines.

Chatbots & SEO

If you have come this far, it’s because you searched in your search engine for something like “chatbots for SEO” or, at least, that search had the words “chatbots” and “SEO.”

Suppose you know what each concept means, great! If you don’t and you want to find out, we’ll explain it to you!

What are Chatbots?

Chatbots are virtual agents that help automate interactions of entities (mostly companies) that receive large contact volumes. In other words, they are conversational agents with Artificial Intelligence that optimize communications between customers and businesses.

They can understand the requests made to them and respond accordingly because they have Artificial Intelligence or AI.

This processing and learning are made possible by NLP (Natural Language Processing) and Machine Learning technologies.

To learn more about the technologies involved in chatbots, you may be interested in the following articles:

Chatbots in Different Digital Channels

Chatbots, as the scalable solutions they are, can be implemented in numerous digital communication channels.

At first, companies solely integrated chatbots on their websites.
However, they quickly realized that the closer they were to customers and prospects, the better.

In other words, if consumers are increasingly on their mobile devices and, consequently, in the communication apps. Then you need to be on those apps as well.

To learn about the advantages of being on different digital channels, you can click here.

But we really want to talk about just one – the website.

Yes, Websites Are Still Relevant!

One might think that because people are mostly on their smartphones, websites are becoming outdated. But this is not true.

Although the number of app users is steadily increasing, the website is what marks your company’s online presence.

Know that a person, before buying a product, looks at the website of the company involved. Therefore, having an appealing and well-positioned website in search engines is halfway to attracting customers.

Besides, customers who don’t know your brand yet may get to know it if (exactly right!) you have a well-positioned site.

But what is this about having my site well-ranked? – you ask.

A website doesn’t get to the first positions of the search engine just because it does.

To get there, it’s crucial to comply with certain parameters.

Since Google is the most used search engine globally, the criteria it stipulates is the one you must pay more attention to.

It makes no sense to follow other engines’ parameters when what interests us is the one that has almost the greatest use worldwide. More precisely, 60 to 70%, with about 3.5 billion daily searches.

What is SEO?

The acronym SEO translates to Search Engine Optimization.

When they say that your website has a good SEO, it means that it’s optimized to meet the parameters or most of them.

This concept is strictly connected with your site’s ranking because the better your SEO is, the more likely you are to reach the top of searches.

How Does Google Know Which Are the Best Websites?

Considering the exorbitant number of websites that exist and are created every day, it would be impossible to analyze them one by one.

For this reason, a classification system was created that, depending on the search performed, presents the best and most complete results.

This ranking system is composed of several algorithms and aims to present optimal results in seconds.

What Are the Criteria for Having Good SEO on Your Website?

The truth is that no one knows what parameters are in Google’s algorithms. However, it’s possible to know some criteria for a better ranking of a web page.

Generally speaking, Google benefits all web pages that are user-centric. That is, they provide the best possible experience.

This user experience is determined according to factors such as:

  • The loading time of the page
  • Ease of use
  • The ease of finding information
  • The fonts used
  • The location
  • Among others.

Still, Google is responsible for changing its algorithms between 500 and 600 times a year!

Most are small changes. When they are major, Google lets us know (unfortunately, without much detail).

However, one certainty we will always have is that it will always favor the user.

But Where Do Chatbots Fit Into This SEO Story?

Very simple. Other factors that Google considers are the “weight,” the domain that your site has, how many people visit, and if other entities identify it as a reliable source, etc.

1) Increasing Website Dwell Time

Taking the first point, it’s possible that many people go to your site but quickly abandon it. In these cases, Google does not see it as a successful case.

Rather, it shows that users did not find what they were looking for or that other factors caused them to abandon, such as page load time.

Having these points optimized, dwell time on a page is a crucial factor, as it shows that the user is interested in the topic presented.

A chatbot can boost these times, as it keeps the user engaged.

The longer the consumer talks to your chatbot, the longer the dwell time on your website will be.

2) Facilitating Searches and Increasing Engagement

Chatbots can be a great tool for finding information.

Imagine a user finds your website and clicks “just to look”. While he/she is navigating, the chatbot detects it and immediately asks him if it needs help or if the user is looking for x or y.

Thus, even if by a virtual entity, the user will feel supported and will benefit from this interaction.

3) Getting Better Ratings

On the other hand, a user who gets what they’re looking for is a satisfied person. The same goes for your customers who come to your website to solve problems through your chatbot.

Having satisfied customers means having good reviews.

These ratings are also an important factor for ranking your website and can be done on numerous platforms, and Google also has this feature.

4) Collecting Data for Improvements

Using a chatbot, you can give the user a satisfaction survey at the end of each interaction.

If the reviews are good, you’re on a good path!

If the reviews are not so good, let your bot collect the suggestions. No one is better than the user to tell you where you can improve.

Believe me, if consumers see that you have listened to their suggestions, they will be pleased!

Conclusions

A chatbot not only benefits your communications with your customers but also your website’s performance.

These virtual agents can be the solution you need to give your search engine ranking a boost. And be the difference between being on the top or on less favorable positions.

Visor.ai solutions, being cloud-based and scalable, are easily integrated into any system, from WordPress to Google Tag Manager.

Whatever system you use, we’ll always have an option for you!

To know more about Visor.ai solutions, contact us!

AI knowledge base
Articles

5 Tips to Create an Effective AI Knowledge Base

For your company’s chatbot to know how to answer your customers’ questions, you need to have a good AI knowledge base.

In this article, you will learn what a knowledge base is, how important it is for a chatbot to operate, and how you can improve it to always get the best results!

What is an AI Chatbot?

A chatbot is an intelligent virtual agent used to optimize communication processes between companies and their customers. However, companies can also use chatbots as internal support for employees.

To learn more about internal chatbots, see the article What Can Internal Chatbots Do for Your Company?

Nonetheless, to be considered intelligent, these agents must possess certain characteristics. In other words, they need certain necessary technologies to have some form of intelligence.

AI for Intelligent Machines

When talking about machines, the term “intelligence” is much debated. We have always been taught that humans are intelligent because of their ability to develop reasoning.

But, nowadays, it’s already possible to program machines to mimic the thinking process of humans.

First, since we are talking about conversational agents, they need to understand and process human language. To this end, they need NLP or Natural Language Processing technology.

For a system to learn the human language, it is fundamental to have linguistic knowledge.

Learn here how important linguistics is in your chatbot.

Second, for the machine to imitate the learning process, it needs Machine Learning technology which, as the name implies, is the one that allows a system to learn by itself.

Find out all the details about Machine Learning here, what its algorithms are and how each type changes the behavior of your chatbot.

What is an AI Knowledge Base?

Well, we can divide knowledge bases into two poles. The first concerns the human knowledge base, and the second the “mechanical” knowledge base, let’s call it.

Generally speaking, a knowledge base is all the information acquired and needed to perform a certain task.

The Human Knowledge Base

The human knowledge base is typically known as “knowledge” only. It’s all the information that a person acquires from birth. All the experiences, the learning that is recorded in the brain.

One kind of knowledge is acquired through transmission, like when our parents tell us “don’t touch the oven or you’ll burn yourself” or when they teach us how to speak.

Another kind of knowledge is intrinsic to us, like learning to walk. Just by the experience of seeing other people walking, the baby, on its own, finds a way to start moving more effectively until, eventually, it starts walking.

The Mechanical Knowledge Base

This type of knowledge is similar to the previous one in the aspect of transmission. That is, if the machine is not fed with data, it will never have any intelligence.

Even if we give it the ability to learn by itself, it will never “join the dots” without information.

So, long before a system or, in this case, chatbot starts to learn, it has to have data it can use – a knowledge base.

Put it like this: in chatbots, a knowledge base is a library that gathers structured and unstructured information.

From the structured information, the bot can categorize the unstructured.

Why Do You Need to Create a Good Knowledge Base?

As we have already talked about, the chatbot needs structured information to interpret and categorize the unstructured data subsequently.

But what differentiates a good database from a mediocre one?

A good database has all the information that is indispensable for the system to do its job well.

Just as we need to know a lot about baking to make a great cake, the same is true for chatbots.

If we want them to have a conversation as similar to humans as possible, then we need to give them all the information they need to make that happen.

Of course, your chatbot won’t need to have the same knowledge as a human being (yet). But it should be an expert on the topic. In this case, the product or service your company is offering.

The Easiest Way to Improve Your Chatbot’s Knowledge Base

“Okay. I already have a chatbot implemented in my company’s digital contact channels. The bot responds well to the questions asked, but it could still be better.” – you think.

Well! You don’t have to wait any longer because the answer is Visor.ai’s platform.

The Visor.ai platform is designed and regularly updated to be as intuitive to use as possible and to users to make the changes they want independently.

During the setup period, Visor.ai provides templates that help the implementation be faster because they already include the basic information for each sector.

But beyond that, the Visor.ai platform offers several tools where you can edit and improve your chatbot or email bot’s knowledge base.

To learn more about automating the handling of incoming emails, click here.

5 Features to Enhance your Knowledge Base

1) FAQs

The FAQs tool is where you can build up, so to speak, the overall interactions of your chatbots.

That is, this is where you include the most frequently asked questions by your customers regarding your products or services.

2) FAQ Conflicts

In the FAQ Conflicts, you can see the conflicts that the chatbot is having between different FAQs.

These conflicts come from phrases often having similar information and the chatbot not knowing which one is the most correct when answering the user.

3) Small Talk

Natural conversation between two humans is not only about scientific and interesting topics. Often it is the so-called “small talk,” conversation without much content, but which is also necessary to maintain a certain climate.

The same has to happen with your chatbot if you want to offer an alternative that is as similar as possible to human dialogue.

It is in the Small Talk of the Visor.ai platform that you define these dialogs. From “Good morning! How are you?” to “Who is your creator?” or “What time is it?”.

All these small talk options have to be present in your chatbot’s knowledge base.

4) Text Analysis

In addition to defining interactions, it’s important to give more detailed knowledge, namely words that have the same meaning or words that, appearing together (compound words), have a certain meaning.

This is where the Synonyms and Compound Words sections come in.

In the first, as the name indicates, you can add synonymous words.

For example, if you are part of an insurance company, you can say that “disaster” is the same as “accident,” “incident,” etc.

In Compound Words, you can teach the bot that it can take expressions like “citizen card” as one entity when analyzing user requests. As opposed to parsing word by word.

5) AI Trainer

Finally, in AI Trainer, you can check your chatbot interactions with your customers.

In this tool, you see all the new user sayings that are not yet in the knowledge base and how the chatbot answered them.

Again, the chatbot can answer questions that are not exactly the ones in your database because it has Artificial Intelligence.

In addition to verification, you can correct the interactions that the chatbot had doubts about and teach it the most appropriate answer. Additionally, you can directly add new FAQs.

This process allows you to increase the intelligence of your bot and make it more efficient.

To learn more details about how to train a successful chatbot, click here!

Conclusions

The Visor.ai team developed the NLP and ML technologies in-house to get the best results and meet our customers’ requirements and needs.

That means that all the knowledge about the human language, its rules, and so on are covered when implementing Visor.ai solutions.

The templates we told you about earlier also cover information related to a certain sector, such as Insurance, Banking, or Marketing.

However, there’s no one better than you to talk about your company or product.

You must include this information in your chatbot’s knowledge base yourself.

If you need help or more information, don’t hesitate to contact the Visor.ai team! We’re always available to hear from you!

Contact us!

If you are interested in this topic, we also suggest you download these ebooks:

machine learning in chatbots
Articles

How Does Machine Learning Work in AI Chatbots?

We humans need to learn new things to expand our level of intelligence. The same happens with AI chatbots through Machine Learning (ML).

Come and find out what ML is, its different algorithms, and how it enables a machine such as a chatbot to learn.

AI Chatbots: What Are They, and What Are They Good For?

The term “chatbot” comes from the word “chatterbot” (chatter + robot), created in the 1990s by Micheal Mauldin.

As the name implies, it’s a conversational robot.

Today, these systems can communicate through written or voice messages.

However, talking robots are often referred to as voice bots, as their primary input is voice commands.

These communication systems are widely used to assist people or companies that receive large volumes of contact and need to automate those interactions.

By being able to automate certain processes, they alleviate the influx of contacts. In this way, they can optimize their handling.

The Types of Chatbots

Chatbots are often associated with Artificial Intelligence (AI). This happens because AI gives them the ability to handle requests without the need for human intervention.

However, some chatbots don’t have AI and, as such, are more basic.

You could say that they’re chatbots based on rules like “if x, then y”.

Non-AI Chatbots cannot understand spontaneous questions and only work based on keywords and decision trees (buttons).

Click here to learn about the different types of chatbots and which one best fits your needs.

How Do AI Chatbots Understand Us?

Chatbots and AI are distinct elements, although they’re related.

As we already mentioned, chatbots need Artificial Intelligence to be able to communicate fluidly. But AI doesn’t only act on chatbots.

AI is a term also applied to any machines that perform tasks typically performed by humans.

In the case of chatbots, there are used technologies related to communication.

Just as we need to learn to read and write and intuitively learn to speak, through the inputs we receive from the people around us, so chatbots need to learn, albeit in a slightly different way than we do.

As the name implies, NLP or Human Language Processing is the technology that enables the understanding and analysis of the large volumes of linguistic data that bots receive.

However, to fully work, chatbots need something more. It’s crucial that the machine can learn automatically from this data. That’s where ML comes in.

What is Machine Learning (ML)?

ML is the other essential technology for a well-functioning chatbot.

The term “Machine Learning” was coined in 1959 by Samuel Arthur, an American computer scientist who pioneered Artificial Intelligence and computer games.

According to IBM, Machine Learning gives systems the ability to learn from experience and improve their decision-making ability and predictive accuracy.

In other words, through the interactions that bots have with users, they can extract information and predict acceptable outcomes (responses). Therefore, they increase their efficiency.

How Does ML Really Work in an AI Chatbots?

Well, just like Natural Language Processing, ML is based on algorithms.

It’s these algorithms introduced into the system that receives and analyzes the data and produces the predictions.

The more data they receive, the more optimized their performance is. So, as time goes by, the bot’s “intelligence” increases.

The Different Types of Machine Learning Algorithms

Without going into too much detail, there’re four types of algorithms: supervised, semi-supervised, unsupervised, and reinforcement learning.

1. Supervised Learning

In supervised learning, the machine learns through examples.

The algorithm is made up of a series of examples of inputs and outputs, and from these, the system has to find a method to arrive at those same inputs and outputs when faced with new data.

The machine identifies patterns in the data, learns, and makes predictions. The operator corrects these predictions, and the process continues until the system achieves a high level of performance.

2. Semi-supervised Learning

This second type of algorithm is similar to the previous one. However, it uses both labeled and unlabeled data.

Labeled data corresponds to a set of training examples with labeled information. These examples consist of pairs with one input and one output.

In this type of learning, the algorithm receives pairs of labeled data and, with the information, it takes from them, learns to label the unlabeled data.

3. Unsupervised Learning

Unlike the previous types, in unsupervised learning, there is no operator.

The algorithm learns to identify patterns and relate information by studying data.

In this type of learning, the algorithm has to deal with large volumes of data and develop a structure for it.

This structuring can be accomplished by organizing groups with similar information (clustering) or by reducing the size, i.e., the smallest number of variables considered to find the exact information.

As with the previous types of algorithms, the larger the volume of data handled, the greater the certainty and efficiency of the system.

4. Reinforcement Learning

Finally, reinforcement learning focuses on regulated processes. These processes provide sets of actions, criteria, and final values.

With the rules defined, the machine tries to find the best result by exploring and monitoring different possibilities.

The Visor.ai Chatbot ML Algorithm

Visor.ai chatbots are all ruled by the type of supervised learning algorithm.

This means that, based on the input and output examples provided to the algorithm, the machine analyzes, identifies patterns, and predicts the results.

Even so, these same results need to be confirmed.

This confirmation and correction (if necessary) can be done through the AI Trainer in the Visor.ai platform.

The AI Trainer is the tool that allows you to confirm and correct interactions that the bot had with users.

In other words, it’s possible to analyze whether the chatbot is giving the right answers to its customers and what was its level of certainty.

In cases where the chatbot didn’t know how to answer or gave the wrong answer, you can teach it. For this, you don’t need any technical knowledge, as the Visor.ai platform is low-code.

After the introduction of these corrections, the system trains the new data set and gets better performance.

Learn more at: AI Trainer: How to Train a Successful Chatbot.

What Are the Benefits of Having a Machine Learning Chatbot?

As we have seen before, we consider that a chatbot has AI when it has technologies that enable it to communicate effectively with a human being.

Companies see many benefits in implementing interaction automation solutions such as chatbots or email bots because:

  • Provide 24/7 service
  • Decrease response time
  • Allow the client self-care
  • Increase your team’s productivity
  • Increase the level of user satisfaction
  • Provide a personalized service
  • Expand your customer base
  • Increase lead generation
  • Reduces cost

In sum, with Visor.ai’s chat and email solutions, you can automate up to about 80 % of the daily interactions your company has.

So, don’t waste any more time, invest in smart solutions. Let’s talk!

If you are interested in this topic, we also suggest you download these ebooks:

AI Insurance Chatbots
Articles

AI Insurance Chatbots: No Pain and a Lot of Gain

Like so many other industries, Insurance has invested in automation solutions, such as AI Chatbots, to digitalize and improve its services.

Learn here in which situations you can use these AI solutions and the benefits of investing in them!

Digital Transformation in the Insurance Sector

More and more talk about companies’ digital transformation and investing in this aspect every day.

But what is digital transformation?

Digital transformation, as the name implies, is the process of integrating technology solutions into all aspects of a company. In other words, it is the evolution of a company in the digital age to keep up with the technologies that are emerging and their accelerated diffusion in the day-to-day life of society.

Why invest in digital transformation?

Today, any company that sticks with only traditional interactions, such as face-to-face and phone service, will not be as successful as digital ones.

Companies have to follow the path their customers take and adapt to those demands.

For these reasons, we have seen a growing investment by companies in solutions for service automation and Digital Marketing.

The case of chatbots for Customer Support or even streamlining internal processes, such as Human Resources or Employee Support, is one example.

To learn how to optimize your Human Resources, click here.

The Covid-19 Push

Little by little, institutions were entering the world of digital transformation. However, the pandemic caused this process to accelerate.

When faced with the impossibility of assisting their customers in person, contact centers were flooded with contacts.

It was then that companies started to show more interest in alternative means of communication, such as chat channels (Facebook Messenger or WhatsApp) and their automation.

Additionally, the automation solution implementation also boosts remote work since platforms like Visor.ai’s are fully cloud-based.

AI Chatbots for Immediate Automation

As we have already mentioned, one of the entrances to digital is through process automation, namely those involving consumers. That is Customer Service.

The simplest way to automate these contacts is with bot solutions, such as AI-enabled chatbots.

What are chatbots?

Chatbots, also called virtual agents, are conversational systems that allow you to streamline recurring, monotonous processes that your team faces daily.

We can separate them into two categories: those without AI and those with AI. That is, those without Artificial Intelligence and those with Artificial Intelligence.

But what is the AI for?

AI is what enables your bot to understand the addressed commands. Through computational technologies such as Natural Language Processing and Machine Learning, the system can understand and learn from the interactions it has with users.

Moreover, it’s Artificial Intelligence that allows a higher degree of efficiency to the system. With this feature, the chatbot can solve the most frequent questions without the need for human intervention.

That said, it follows that chatbots without AI are more limited.

They’re not able to answer simple questions but work based on decision trees. Whatever the question is, the client always talks to a human assistant.

Use Cases: What can AI chatbots do for insurers?

As we have already told you, chatbots can solve the most frequent questions your contact center receives. However, we have not yet given concrete examples.

1) Consumer Education and Simulations

In addition to FAQs, chatbots can educate customers regarding the products and services your company offers.

With the customer’s profile information and the insurance they are interested in, the virtual agent can inform the user of the different options available.

2) Procedure Execution

AI chatbots can answer frequently asked questions, but they can also help consumers perform procedures. Namely, payments, adhering to services, or declaring claims.

They can indicate which steps to follow so that the customer can complete the request independently.

3) Requesting Documents

One of the most recurrent cases in insurance companies is requesting a copy of documents that prove insurance. More specifically, the proof of car insurance.

With just a few authentications from the customer, the bot can immediately send the document without any human intervention.

4) Claims Processing

Intelligent systems can be programmed to resolve claims and follow up on complaint processes that have already been initiated.

5) Sending Notifications

According to studies, 68 % of consumers have a more favorable view of companies that proactively contact them through notifications. In other words, they prefer companies to inform them of updates rather than having to look for them themselves.

6) Feedback Gathering

The same studies say that 77 % of respondents hold institutions that ask for and accept customers’ feedback in higher regard.

Furthermore, having your customers’ opinions is a very efficient way to know where you can improve.

Since customer satisfaction is one of your primary concerns, it’s essential to take their suggestions into account to offer the best possible service level.

The Benefits of Implementing AI Chatbots

Automation

Automation is one of the most relevant points of these solutions.

The possibility of having a system that automatically solves specific procedures is a weight off your team especially, if the processes are repetitive and monotonous.

24/7 Service

The introduction of chatbots makes permanent self-care possible. Whatever the time of day or day of the week, your customers can resolve their questions themselves with the help of the virtual agent.

Engaging with Customers

When the consumer is browsing your website, the chatbot can pop up and interact with the customer.

This way, it can find out more information about what product or service they are looking for and direct them to the best-fit option.

Additionally, it can suggest products that relate to what the user is looking for.

Expanding Digital Contact Channels

You can implement chatbots in any communication platform – for example, Facebook Messenger or WhatsApp – because they’re modular and scalable solutions.

Expanding your company’s contact channels allows you to decrease the inflow of contacts. That is, the more means of communication you provide, the more divided the requests will be.

Increased Leads

Related to the previous point is increasing leads.

Very briefly, leads are the people interested in your product; potential customers.

By expanding your communication channels, you can increase business leads because you grow the range of customers. In this case, more digital consumers.

Data Collection

As we mentioned earlier, companies are investing in Digital Marketing. However, to advertise, you need consumer data. What product they’re looking for, what age group they belong to, etc.

Through chatbots, it is possible to collect this information to be used later, either in bot notifications, email marketing campaigns, among others.

Personalization

In parallel to data collection, there is the possibility to segment customers by their demographic characteristics.

By creating these profiles, you can, through the chatbot platform, define triggers and send broadcasts to your customers. That is, send campaigns explicitly designed for a particular type of consumer.

Find out here how to get the most out of Triggers and Broadcasts.

Cost Reduction

Studies by Juniper Research show that AI and chatbots will significantly impact claims management in the insurance industry. That impact will lead to cost savings of about $1.3 billion by 2023.

More Than AI Insurance Chatbots that are Email Bots!

We have been talking only about chatbots with Artificial Intelligence. However, the growing trend is the implementation of email bots.

While chatbots have the function of automating chat channels, email bots automate the email channel.

Every day large volumes of emails arrive at companies, making it difficult to handle so many requests.

However, an email bot can help with this.

With different levels of processing, an email bot can read and categorize incoming emails and their attachments.

To process the attached documents is used OCR or Optical Character Recognition technology.

Besides, it can forward it to the correct department. Furthermore, you can request missing information before delivering it.

Visor.ai’s inbound email automation solution can be implemented on any CRM platform, such as Salesforce.

Learn more about this solution in Email bots: How to Automate your Mailbox.

Give your insurance company a push in its digital transformation with Visor.ai automation solutions!

Let’s talk!