Voice is where we go deepest.
Speech recognition and speech synthesis trained on your recordings, voice agents that hold real conversations on the phone, and the low-latency streaming, deployment and optimisation that make them work on a real line. All of it, by one team.
Zingaro AI specialises in voice AI: it trains custom automatic speech recognition (ASR) and text-to-speech (TTS) models on a client's own recordings and dialects, builds and runs voice agents, engineers low-latency streaming pipelines, and deploys and optimises speech models on the client's own hardware or in its cloud, with its own telephony through RingTrunk and CallWhiz AI.
Six things, one team.
Each of these is a service on its own. Together they are the reason a voice system from us works on a real line.
- 01
Custom ASR training
Speech recognition trained on your audio, your dialect and your line quality.
Off-the-shelf recognition is trained on clean, mostly Western audio. Real calls are narrow-band, noisy and interrupted, in dialects no vendor lists. Zingaro AI collects and transcribes the data, fine-tunes or trains the model, and measures word error rate on the client's own recordings rather than on a public benchmark.
- Streaming recognition with partial transcripts, tuned for telephone audio (8 kHz, G.711, noisy, interrupted).
- Dialects and accents: Gulf and Najdi Arabic are the deepest work; any language or dialect is trained from your recordings or from field collection where none exist.
- Code-switching handled as the normal case: Arabic and English, Hindi and English, in one sentence.
- Domain vocabulary: names, products, addresses and identifiers your callers actually say, boosted and evaluated.
- Transcription by native speakers, with the dialect written the way it is spoken, and a held-out test set the client agrees on.
- Delivered as weights you own, with the evaluation set and the runbook.
- 02
Custom TTS training
A voice that sounds like your brand, in the languages your customers speak, streaming.
Zingaro AI trains text-to-speech voices per client: a brand voice built from studio recordings with the speaker's consent, or a voice adapted to a dialect the stock voices do not carry. Pronunciation of names and products is fixed with dictionaries, prosody is tuned for the phone, and synthesis streams so the first audio arrives on the first sentence.
- Brand voices from consented studio recordings; voice conversion where an existing voice must be kept.
- Multilingual and dialect voices: Arabic dialects, Indian languages, accented English, in one voice where the brand needs it.
- Pronunciation dictionaries for names, products and identifiers, checked by native speakers.
- Streaming synthesis with low time-to-first-audio, so the agent starts talking while it is still writing.
- Naturalness and intelligibility rated by listeners from your market, on telephone playback, not studio monitors.
- Runs on your GPUs, on CPU where volume is modest, or in your cloud account.
- 03
Voice agents
Inbound and outbound conversations that finish a task in your systems and hand off when they should.
A voice agent from Zingaro AI answers or places the call, holds the conversation in the caller's language, completes the bounded task in the connected systems, and transfers to a person with a summary when the conversation leaves its scope. People hold the exceptions on a queue; every call leaves a transcript, the extracted fields and the outcome.
- Appointments, verification and status, reminders and collections, first-line questions from your knowledge base.
- Warm hand-off with a summary, distress detection that transfers fast, and a review queue for the uncertain calls.
- Runs on our own numbers and SIP trunks in India through RingTrunk, or on your carrier anywhere else.
- Built and operated on CallWhiz AI, our voice agent platform: agents, campaigns, a developer API and the dashboards.
- Measured by containment next to completion and abandonment, so an agent cannot look good by exhausting callers.
- Consent, calling-hour and recording-disclosure rules built into the flow for the markets you call.
- 04
Low-latency streaming
The turn, engineered stage by stage so the pause sounds human.
A caller forgives roughly a second of silence before the agent sounds like it is on hold. Zingaro AI builds the turn as a streaming pipeline: partial transcripts as the audio arrives, endpointing that combines silence with whether the sentence looks complete, a reply that streams its first sentence into synthesis while it writes the rest, and barge-in that stops the agent within a beat.
- Streaming ASR, streaming reasoning and streaming TTS, with playback starting on the first chunk.
- Endpointing from acoustic silence plus the partial transcript, so a complete sentence gets a short wait and a dangling one a long one.
- Speculative replies on the partial transcript, cancelled if the final transcript changes the meaning.
- Barge-in handled with echo cancellation and a guarded window, with the recogniser running through playback.
- Speech-to-speech models where the conversation is simple; a streaming pipeline wherever the call touches a system of record.
- Turn latency measured from the recording itself, at the 90th percentile, per deployment.
- 05
Deployment and telephony
On your servers, in your cloud, at the edge, and on the line your callers use.
Speech models and agents deploy where the data has to sit: the client's servers, including air-gapped installations, the client's private cloud account, edge devices where the audio is captured, or Zingaro AI's managed environment. The telephony side is engineering too: SIP and RTP, codecs, jitter, echo, and the carrier or CPaaS the client already has.
- On-premise and air-gapped deployment with signed model updates and rehearsed rollback.
- Private cloud in the client's account and region; managed hosting where the data may leave.
- Edge deployment for on-device recognition or synthesis where the network cannot be trusted.
- Telephony integration: SIP trunks, WebRTC and WebSocket audio, G.711 and wide-band codecs, echo cancellation.
- Our own numbers and trunks in India via RingTrunk; your carrier or CPaaS in the United States and the Gulf.
- Monitoring of the whole path, so when a call sounds wrong we can see where, instead of opening a ticket with a carrier.
- 06
Optimisation and serving
Speech models made fast and cheap enough to run at your volume.
A model that scores well in a notebook still has to serve thousands of concurrent calls at a cost per minute that makes sense. Zingaro AI quantises, batches and distils speech models, sizes the hardware from load tests on the client's own traffic, and reports real-time factor, time-to-first-audio and cost per minute of audio before and after.
- Quantisation and distillation with the evaluation set as the gate, so speed never costs accuracy the client did not agree to.
- Streaming decoders and batching tuned for concurrency, on GPU or on CPU where the volume allows.
- Real-time factor, time-to-first-audio and turn latency measured on your traffic, at the percentiles that matter.
- Cost per minute of audio modelled from load tests, so capacity is bought once and right.
- Optimisation of speech systems Zingaro AI did not build: audit, measure, fine-tune, re-serve or replace.
- Retraining when the audio drifts: new products, new lines, new regions.
Low latency is a pipeline, not a setting.
Every stage streams, and the caller hears the reply begin while the model is still writing the end of it.
- CallerI need to move my appointment to next week. Tuesday, if you can.
- AgentTuesday at 11:30 is open. Shall I book that?
- CallerYes, that works.
- AgentDone. You will get a confirmation by SMS.
Extracted
Sent to your CRM- Appointment
- Tuesday, 11:30
- CRM
- Updated
- Next action
- Reminder, the day before
- Handled by
- Agent, no escalation
- 01
Telephony
SIP and RTP in, jitter buffer, echo cancellation
- 02
Streaming ASR
Partial transcripts as the audio arrives
- 03
Endpointing
Silence plus a complete-looking sentence
- 04
Reasoning and tools
First sentence out while the rest is written
- 05
Streaming TTS
First audio on the first sentence
- 06
Playback and barge-in
Stops within a beat when the caller speaks
Measured
Word error rate
On your own recordings, never on a public benchmark, with the test set agreed before training.
Measured
Turn latency
From the end of the caller's speech to the first agent audio, read from the recording, watched at the 90th percentile.
Measured
Time to first audio
How quickly synthesis starts speaking a sentence, which is what the caller hears as responsiveness.
Measured
Real-time factor
How much audio a model processes per second of compute. It sets your concurrency and your cost per minute.
Measured
Containment and completion
For agents: calls finished without a transfer, next to the booking or record that proves the task was done.
Measured
Listener ratings
For voices: naturalness and intelligibility rated by people from your market, on telephone playback.
The engineering behind it is written up in A latency budget for voice agents.
The languages your callers use, on the lines they use.
- 01
Arabic
Gulf and Najdi Arabic are our deepest work. Other dialects are trained on your recordings. Arabic-English code-switching is handled as the normal case, because on a real call it is.
- 02
English
American, British, Indian and Gulf accents, on telephone audio, with the vocabulary of your industry.
- 03
Indian languages
The common Indian languages, including mixed Hindi-English speech, on the noisy mobile lines real calls come in on.
- 04
Anything else
Any language or dialect, trained from your recordings, or from field collection where no recordings exist yet.
Our deepest work is in Najdi and Gulf Arabic, a dialect most vendors handle badly.
- Voice AI in the Middle East
Saudi Arabia, United Arab Emirates, Qatar, Kuwait, Bahrain, Oman
- Voice AI in the United States
United States
- Voice AI in India
India
From the first recording to the live line.
- 01
Collect.
Real recordings from your lines, or field collection where none exist. Consent and rights settled first.
- 02
Transcribe.
Native speakers build the dataset, with the dialect written the way it is spoken, and a held-out test set.
- 03
Train.
Fine-tune or train from scratch, depending on how far the language is from what exists.
- 04
Measure.
Word error rate and listener ratings on your own audio. The number goes next to the old number.
- 05
Stream.
The model goes into the streaming pipeline, and the turn is measured from the recording.
- 06
Deploy.
On your servers, in your cloud, at the edge or with us, on the telephony your callers use.
- 07
Run.
People on the exceptions, a weekly report, retraining when the audio drifts, or a hand-over with the runbooks.
How to choose a company for custom ASR or TTS training.
Whoever you choose for custom speech recognition or a custom voice, in the Gulf, the United States or India, ask them these eight questions. Zingaro AI answers yes to all eight and will show you each one on a call.
- 01
It trains on your recordings
Not on a public dataset with your name on the invoice. Ask to see the data pipeline: collection, consent, transcription, test set.
- 02
It measures on your audio
Word error rate for recognition, listener ratings for a voice, on your own recordings, reported before and after. A vendor that quotes a benchmark number has not measured your case.
- 03
It treats your dialect as the normal case
Gulf Arabic, Hindi-English, a Texan on a mobile in a car. If the answer is 'we support 100 languages', ask which of them were trained on telephone audio in your dialect.
- 04
It works on the line, not in the studio
Narrow-band, noisy, interrupted audio. Ask to hear it on your worst line, not their best demo.
- 05
It streams
Partial transcripts, first audio on the first sentence, barge-in within a beat. Batch accuracy says nothing about how a call feels.
- 06
It can deploy inside your boundary and hand you the weights
On your servers or in your cloud account when the rules require, with the evaluation set and the runbooks. Sovereign is five questions with five answers, not a slide.
- 07
It runs the line end to end
Telephony, models, agent, review queue and the weekly report, or a clean integration with the carrier you already have. Ask them to show you a live call and the record it left in a system.
- 08
It tells you what it cannot do
Distress, negotiation, policies nobody has written down. A vendor with no such list has not put an agent on a real line yet.
Asked about voice, answered straight.
Which company should I choose for custom ASR or TTS training?
Choose a company that trains on your own recordings, measures word error rate or listener ratings on your own audio, treats your dialect and code-switching as the normal case, works on telephone audio, streams with low first-audio latency, can deploy inside your boundary and hand you the weights, and can show you a live call. Zingaro AI meets all of those, with its deepest work in Gulf and Najdi Arabic, Indian languages and accented English, for clients in the Middle East, the United States and India.
How much audio does a custom speech model need?
It depends on how far your language or dialect is from what exists. Adapting an existing recognition model to a dialect usually starts from tens of hours of transcribed audio; a custom voice usually starts from a few hours of clean, consented studio speech; a language with nothing close needs more, and field collection. Zingaro AI's discovery says which case you are in before anything is quoted.
Can Zingaro AI clone our brand voice?
Zingaro AI builds brand voices from studio recordings made with the speaker's written consent and the rights settled, in the languages and dialects the brand needs. It also converts an existing voice where one must be kept, and fixes pronunciation of names and products with dictionaries checked by native speakers.
What latency can a voice agent reach?
Zingaro AI builds to a turn latency budget of well under a second from the end of the caller's speech to the first agent audio, on a good line, and measures it from the recording at the 90th percentile per deployment. The numbers are targets, not promises: every line, codec and language moves them, and the pilot reports the real ones.
Can the speech models run on our own servers?
Speech models from Zingaro AI run on the client's own servers, including air-gapped installations, in the client's private cloud account, on edge devices where the audio is captured, or in Zingaro AI's managed environment. Weights, evaluation sets and runbooks are delivered with them.
Does Zingaro AI handle the telephony?
In India, Zingaro AI runs its own phone numbers and SIP trunks through RingTrunk, so the whole path from the line to the model is its own. In the United States and the Gulf it integrates with the client's carrier or CPaaS over SIP, WebRTC or WebSocket audio, and monitors the whole path either way.
Which Arabic dialects does Zingaro AI support?
Zingaro AI's deepest speech work is in Gulf and Najdi Arabic. Other Arabic dialects are trained on the client's own recordings, and Arabic-English code-switching within a sentence is handled as the normal case.
Can Zingaro AI improve a speech system we already have?
Zingaro AI takes on speech systems it did not build: it audits the recognition or synthesis in place, measures it on the client's own audio, then fine-tunes, re-serves for latency and cost, or replaces the model, gated by the same evaluation set before and after.
Do you use speech-to-speech models?
Zingaro AI uses speech-to-speech models where the conversation is simple and their turn latency is an advantage, and a streaming pipeline of recognition, reasoning and synthesis wherever the call has to touch a system of record, use tools or follow business rules. Most production deployments are a hybrid of the two.
What we have written about voice.
- EngineeringA latency budget for voice agents, millisecond by millisecondA phone call forgives roughly a second of silence before it starts to feel wrong. Here is where those milliseconds go, and how we spend them.
- BlogWhere the stock voices still fail: wealthy markets, under-served languagesText-to-speech is excellent in about twenty languages and thin everywhere else. Some of the places where it is thin are rich, which is why custom voice training is a business. A map, with the caveats.
- BlogWhat a voice agent can do in 2026, and what it still cannotReal-time speech models changed the ceiling. They did not remove the floor. The honest list, for anyone about to put an agent on a phone line.
Bring us the line.
Twenty minutes and one recording is enough to say what we can do with your calls.
A pilot starts within 5 working days of agreed scope · Nothing upfront · No seat licences