Every call is data. Put it to work.

Vivitec Voice Labs

An AI agent answers your phone, routes on what the caller actually says, captures the details and confirms them out loud. When the call ends a second model re-reads it, cleans up what was captured, scores it, and writes the result into the systems you already run.

What it does

What Voice Labs does.

Grouped the way a call runs: while the caller is on the line, once they hang up, and what you build on top of both.

While the caller is on the line

Intent-driven routing: Routed by what the caller says, not which key they pressed.
Live lookups: Checks your site, price list and schedule mid-call instead of reciting a script.
Structured capture: Names, numbers and details taken and read back while they are still there to correct them.
Warm handoff: Transfers to a person and stays silent for the whole ring.
Answering by hours: Which agent picks up, by time of day and day of week.

Once they hang up

Second-pass cleanup: The whole call re-read with the ending known; misheard details corrected.
Sentiment scoring: Turn by turn, not one label stuck on the whole call.
Document intelligence: Attachments, forms and photos of paperwork read into fields.
Follow-up tracking: Tasks with an owner and a due time, not a line in a weekly report.
CRM writeback: Contact, summary and disposition into the system you already run.

What you build on it

Conversational agent builder: Describe the agent in plain language; it drafts one and you publish it.
Your own AI, connected: Claude, ChatGPT or Copilot read your calls over MCP, with your sign-in.
Agent-to-agent handoff: Scheduling, quoting and collections agents, each with its own tools and limits.
Draft, then publish: Every change to how an agent behaves waits for a person to approve it.
Every call reviewable: Transcribed, scored and searchable, by you or by whichever assistant you point at it.

On the call, and just after

Two models, because it is two different jobs.

The model on the call is committed turn by turn — it has to speak before it knows how the call ends. The one that runs afterwards has the whole thing in view, which is what makes the cleanup possible.

While the line is open

Answers and holds the turnBarge-in, no dead air, and silence held for the whole ring when a call is being handed to a person.
Confirms what mattersNames, numbers and spellings read back to the caller while they are still there to correct them.
Looks things up liveYour site, your price list, your schedule, your systems — checked during the call rather than recited from a fixed script.
Routes with a reasonWho it went to, and the reason it went there, recorded as part of the call.

After it ends

Re-reads the whole callWith the ending known, the beginning means something different. A second pass reclassifies what was captured live and fixes what was misheard.
Scores how it wentSentiment turn by turn, not one label stuck on the whole call.
Reads what was sentDocument intelligence on the attachment, the form, the photo of the paperwork.
Writes the recordThe follow-up, the contact, the summary — into the systems your team already has open.

Where it goes

Where the call and its data go next.

Each part of a structured call can be handed to whatever already does that job — the phone system, the CRM, a task list, or the next agent in the chain.

The call itself
Transferred, queued or held — to the right desk, with the reason it went there recorded alongside it. The caller hears nothing from the agent while the destination rings.
The record
Contact, summary and disposition written into the CRM your team already has open, under the account it belongs to rather than as a loose note.
The task
Follow-ups land as work with an owner and a due time — not a line in a report somebody reads on Friday.
The next agent
One agent hands to another. A scheduling agent takes the booking, a quoting agent prices the job, a collections agent works the balance — each with its own tools, its own limits, and the same call behind it.

Ask it anything

Connect it to the AI your team already uses.

The platform speaks MCP, the open standard for connecting tools to AI assistants. Point Claude, ChatGPT or Copilot at your calls and ask in plain language — which accounts are unhappy, what got promised last week, who still needs calling back. Build your own agents on the same interface. Your sign-in, your permissions, your data.

Review calls, build agents, ask questions

These are the actual tools the connector exposes. What an operator can read, an assistant can read; what an administrator can change, it can propose as a draft for a person to publish.

list_calls get_call list_followups read_agents read_agent_prompt read_routing read_hours read_destinations read_agent update_agent_draft

Two ways to build an agent

Describe it, in the platformThe builder interviews you in plain language, drafts the agent, and hands it back for a person to publish.
Or bring your own AIPoint Claude, ChatGPT or Copilot at the same connector and build against it directly. Same permissions either way.
Attached to your systemsThe platform writes where the work already happens. It is not a place your team has to remember to visit.
It cleans up the phone system you ownHours, routing and destinations stay where they are. Voice Labs answers, sorts and hands off — it does not ask you to replace the thing that already works.
The data is yoursEvery call, transcript and captured field is readable and exportable. Ownership is the point; the connector is just what ownership looks like in practice.
A person stays in the loopChanges to how an agent behaves arrive as a draft. Someone publishes them.

Start here

Start with the phone. Expand into the rest of the stack.

It is the best first move in an AI programme we have found: real volume, real value, and a pipeline that is already reaching into your systems by the time you are ready for the second project.

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