Chat AI Agent
Chat AI Agent takes your customers' messages on WhatsApp, and the same AI agents work on your website and your other messaging channels. It answers from your own knowledge, and when a person is needed, it hands over the whole conversation.
What goes wrong
A chat agent fails quietly. The customer closes the tab, and nothing in your reports says why.
The agent quotes a price or a policy you changed weeks ago, because nobody updated the document it reads.
Your customer writes that they want to talk to someone and gets the menu back.
The chat reaches your team without the conversation, so the first thing a person asks is something the customer already answered.
Most chats are never read by anyone. You find out the agent has been getting something wrong when the same question starts reaching your phone line.
What the platform does
Chat Agent runs on the same platform as Voice AI Agent. Your customer sees the widget; behind it sit the knowledge the agent answers from and the team that takes over when it can't help.
The agent answers from a knowledge base built from your own documents and kept in sync with them. Check integrity and Compare with index show whether the index the agent reads still matches the files in each folder, which catches the price list that was replaced but never reindexed.
We maintain it throughout deployment and then hand it to your team, so the answers stay yours to correct.
Every agent has its own page, and you talk to it there first, in the Chat tab or by voice. The page also lists what hasn't been checked yet, from the latest compliance check to a test suite Nexa can write for you and Nexa's review of the results.
Publishing moves the flow from the development environment to live, and each publish goes into a history you can read back.
The widget carries your agent's name, its avatar and your brand colour, in a light theme, a dark one or whichever the visitor's system uses. You preview it on desktop and on mobile before it goes live.
When a chat needs a human, it moves to live chat and is routed to the right department with everything the customer already wrote. Your team works from the quick answers and forms you define, inside the working hours you set, and nobody asks the customer to repeat themselves.
An Issue Agent reads conversations against criteria you write in plain language and sorts what it finds by severity. A wrong booking confirmation can be critical while an extra question is low. You also write what not to flag, which keeps the list short enough to act on.
Watchtower counts the flags across every conversation in progress, and a supervisor can step in from there.
Our clients
From kickoff to go-live, you work with named people who know your project, whether you come to us directly or through a partner.
We agree on what's in and what's out before we start, so everyone knows what success looks like.
Performance metrics are part of the build, so you see results from your first day in production.
We test end to end, then your team validates it in real conditions before launch.
We train your people to run the platform confidently, and we stay by your side for as long as you need us.
The models generate each answer in the moment and can occasionally fail. Visor's work is to contextualise them, apply controls and tune continuously. The solution runs on specialist providers who, like any provider, do not guarantee total availability. That's why the handover to your team gets as much care as the answers: when the agent can't help, a person can.
