Utilities
On a normal day your queue is predictable. Then a storm takes out a substation and every household on that line calls at once, most of them to ask the same question. Voice AI Agent answers them with what you already know about the outage, and hands the calls that need a person to your team with the details already collected.
What goes wrong
Your contact centre is staffed for an average day, and your customers call on the worst one. The calls that pile up are mostly simple, which is what makes the wait so hard to justify.
During an outage most calls ask when the supply comes back, and each one waits in line behind the others.
A customer reporting a smell of gas waits behind a queue of billing questions.
Your customer reads the meter number to the phone menu and again to the advisor, because nothing came through with the transfer.
A tariff change reaches every letterbox in the same week, and the calls asking why arrive together.
What the platform does
Visor's AI agents take the calls a peak is made of, and the platform shows you whether they're holding up while it lasts. When a call needs a person, it reaches one with the details already taken.
You write the scenarios an outage really produces, like the caller who wants a restoration time you don't have yet, or the one reporting a hazard who has to reach a person straight away. Each one runs against the agent repeatedly, with success criteria you set, so you know how it behaves before the next storm.
On an outage day the agent leans on your telephony and on your own systems, such as the outage map and the customer account. The platform measures each service separately, latency percentiles included, and counts the requests that came back empty, so a slow answer has a cause you can name.
Watchtower shows every call in progress. A supervisor can listen in and press Take on the call that needs a human, like a customer who depends on powered medical equipment. The transcript goes with it, so nobody asks for the account number twice.
Many customers check your website or message you on WhatsApp before they pick up the phone. Chat AI Agent answers them there from the same knowledge base, kept in sync with your documents, and Compare with index shows when a replaced document was never reindexed. The tariff the agent quotes is the one in this week's letter.
Quality & Insights AI Agent scores your advisors' call recordings against your own scorecard, all of them or a share you set, taken straight from your contact-centre or CCaaS platform. A peak week gets reviewed as fully as a quiet one. Scores by team show where the rush wore down the answers, and a supervisor opens the calls behind any number. The same pass records why customers called, so you see which reasons rarely resolve on the first call.
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. Judge the AI Agent by the standard you would apply to an experienced colleague: consistent and improving performance, not infallibility. The go-live is the start of the improvement, not the end of the project.
Agents on the phone that take the routine calls of a peak and hand over the rest.
Your advisors' call recordings scored against your own scorecard, a busy week as fully as a quiet one.
The same answers on your website and on WhatsApp, from the same knowledge.
