Connects to the PBX, not around it
Yeastar and compatible SIP systems register from a form, and the business keeps its provider, its numbers and its call plan.
AI voice agent case study
Vocale
An agent that answers a business's phone line, finds the answer in that business's own documents, and opens the support ticket before the caller has hung up — on the numbers they already own, and on their hardware if they want it there.
- IndustryInbound support and telephony
- UsersSupport teams on a Yeastar or SIP PBX
- CoverageEvery call, around the clock
- ServicesProduct Design, Development, AI
Overview
Vocale puts an AI agent on a phone line a business already has. A customer dials the number they have always dialled; the agent picks up on the first ring, speaks their language, answers from the company's own manuals and policies, and — when the answer is really "somebody needs to look at this" — files a support ticket with the details already collected.
Nothing about the phone system changes. The business keeps its provider, its numbers and its call plan; a Yeastar or compatible SIP platform is connected once from a form, and the trunk and call routing are provisioned behind it. From there the work is uploading the documents the agent should know, writing the few sentences that set its manner, and testing it in a browser until it sounds right — all of it before a single real call is routed to it.
The decision that makes or breaks the economics is where the models run, so the platform ships two engines behind one product. On the hosted tier, speech, reasoning and voice come from a third-party API and every minute is metered. On the self-hosted tier all three run on a GPU under the business's own control, no audio or document leaves the building, and a call costs electricity. Switching between them is configuration; the agent behaves the same either way.
- Next.js 15
- TypeScript
- Tailwind CSS
- Supabase
- PostgreSQL
- LiveKit
- WebRTC
- SIP telephony
- Python
- vLLM + Qwen3-8B
- Faster-Whisper
- Coqui XTTS-v2
- Pinecone
Project video
vocalePlug in the phone line. It answers.
A walkthrough of Vocale, from connecting a phone system and uploading a manual through to a live call that answers the question and files the one it could not.
Key capabilities
Answers the phone
Connects to the Yeastar or SIP system the business already runs, so calls reach the agent on the numbers customers have always dialled.
Grounded in your documents
Manuals, policies and price lists are uploaded, indexed and searched at the moment of the question — so the answer comes from the business's own material rather than the model's memory.
Opens tickets mid-call
When a caller needs a person, the agent gathers the subject, the contact and the urgency while it still has them on the line, then files the ticket itself.
Knows who is calling
An existing customer database connects read-only, so an inbound number is matched to an account before the agent says a word.
Two engines, one product
The same agent runs on a hosted model API or entirely on a private GPU. The business picks on cost and on where its data is allowed to go.
The challenge
The phone rings at seven in the evening. The answer is in a PDF on the shared drive. Nobody is there to read it.
A support line is only as available as the people answering it, and the questions arriving on it are overwhelmingly the same handful: what are your hours, is this covered, how do I reset it. The answers are already written down — in a manual, a policy, a price list — just not anywhere a caller can reach and an operator can find while somebody waits. Putting an AI on the line fixes the availability half of that. Renting one by the minute quietly replaces it with a cost problem, because the better it works the more it is used, and the more each month costs.
Calls outside office hours
Evenings, weekends and holidays go to voicemail — and what lands there is mostly the routine enquiry a person would have closed in a minute.
Answers nobody can reach
The information exists in documents, but not in any form somebody can consult with a caller waiting on the line.
Priced by the minute
Managed voice-AI platforms bill per call minute, so the bill grows with adoption — the wrong incentive to put on a support line.
Our solution
One agent, on the line you already have.
Vocale sits between a business's phone system and its knowledge. The PBX connects from a form and the routing is provisioned behind it. Documents are uploaded and indexed. The agent's manner is set in plain language rather than in code, and the whole thing can be rehearsed in a browser before a real call reaches it. Once it is live, everything it did is on the record — the transcript, the searches it ran, the tickets it opened — so the team can judge whether it is doing the job before trusting it with more of one.
Retrieval before it speaks
A question that needs a fact triggers a search across the indexed documents, and the reply is assembled from what came back — with nothing found being an answer the agent is allowed to give.
Hosted or self-hosted, same behaviour
Speech, language and voice run behind a third-party API or on a private GPU. Moving between them is configuration, not a rebuild.
How it works
Test it before a customer does
A sandbox that runs the whole pipeline in the browser. Pick a caller, start the call, and the transcript arrives live beside it as the agent hears and answers. Every session it has ever handled — browser or phone, inbound or outbound — is one click away in the rail on the left.
The documents it answers from
Files are dropped straight onto the page, then parsed, split and indexed. Each row reports how many pages went in and how many searchable pieces came out, so it is obvious at a glance when a document is ready to be quoted on a call and when it is still being worked on.
What it could not answer becomes a ticket
The agent collects the subject, the customer and the urgency while the caller is still on the line and files the ticket itself, transcript attached. Support opens the queue to a list of real problems in the caller's own words instead of a column of missed calls.
It knows who is calling
An existing customer database connects read-only, with a mapping step for whichever columns hold the name and the number. From then on an inbound call is matched against it before the agent speaks — and the records stay where they are. Vocale reads them; it does not become the place they live.
Numbers, assigned from the console
Telephony is the one part a business should not have to get right alone, so provisioning is an operator job rather than a self-service form. Each number is registered, pointed at an organisation and switched on from here — which doubles as the fastest way to see which tenants are actually taking calls.
What every minute costs
Spend is metered the way the models bill it — caller speech, agent speech and replayed history, broken out per model and per organisation. It is what turns the choice between a hosted API and a private GPU into a decision with a number attached rather than an argument.
Impact & outcomes
Answered on the first ring, and priced like software.
What matters on a support line is not accuracy in the abstract — it is whether the call was answered and whether the answer was right. Vocale answers all of them, at any hour, in the caller's language, and leaves a transcript behind so the second question can be settled. The cost below is what the platform metered on the hosted tier over a month of real calls; the self-hosted tier moves that line onto hardware the business already pays for, and the per-minute figure stops moving at all.
- 24/7
- Call coverage, with no rota and no queue
- $0.06
- Metered cost per call minute, hosted tier
- 6
- Languages the agent can be switched to
- 2
- Ways to run it: hosted API or private GPU
System design
What a business can do from the dashboard
Anatomy of a single spoken turn
What we had to solve
Being interrupted mid-sentence
Solution: Callers talk over an answer the moment they have understood it, and an agent that keeps going sounds broken. Voice activity detection cuts the outgoing audio as soon as the caller speaks, then truncates the agent's own transcript to what was actually heard — so the conversation continues from the call the caller experienced rather than the one the system had planned.
Silence while it thinks
Solution: Searching the documents takes long enough to read as a dropped call. The agent fires a short, natural filler half a second in and cancels it if the search returns first, which buys retrieval its time without any of it landing as dead air.
Text that does not read aloud
Solution: Written for a screen is not written for a voice: currency amounts, dates as digits, acronyms. A normalisation layer rewrites amounts, dates, times and abbreviations into their spoken form, per language, before they ever reach the speech model.
One GPU, several conversations
Solution: A live voice session holds its models in video memory, so capacity is bounded by VRAM rather than by raw compute. Sessions are budgeted per card and the workload is pinned across cards explicitly — left to default pooling, speech and language work land on the same GPU and starve each other.
Questions
No. Vocale connects to the phone system you already run — Yeastar and compatible SIP platforms — and calls keep arriving on the numbers your customers already have. The connection is made once from the dashboard, and the trunk and routing are provisioned behind it.
Whichever way suits you. The same agent runs on a hosted model API, which is the quickest way to start, or entirely on a GPU under your control, where no audio, transcript or document leaves your infrastructure. It is a configuration choice, and it does not change what the agent can do.
It answers from your documents rather than from memory. A question that needs a fact triggers a search across everything you have uploaded and the reply is built from the passages that come back. When nothing relevant is found, saying so and offering to open a ticket is the correct answer, and the one it gives.
It hands over. The agent collects the subject, the contact and the priority while the caller is still on the line, files a ticket in your queue and attaches the transcript — so whoever picks it up starts from what was actually said rather than from a callback request.
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