For the founder building a voice product.
A demo investors like, and a dialect, a latency or a cost-per-minute problem between it and a business.
Zingaro AI works with founders building products where the voice is the product: AI receptionists and phone agents for a vertical, language-learning and reading apps, in-car and in-device assistants, dubbing and narration tools, accessibility products, and voice platforms in Arabic, Indian languages or accented English. It trains custom text-to-speech voices and speech recognition for the founder's language and use, engineers the streaming pipeline so the turn feels human, runs it on the device where needed, and provides the telephony when the product is on the phone.
Is this you?
- You are a founder or CEO with a product where users speak and the product speaks back, and the stock voices and recognisers do not sound like your market or hear it.
- You have a demo that investors like and a latency, a dialect or a cost problem that stops it from being a business.
- Your team is product engineers; nobody has trained a speech model or run a SIP trunk.
- You are measured on retention, on cost per minute against price, and on whether the next round happens.
What you are trying to get done
- 01
A voice that is yours: your brand, your language, your dialect, from consented studio recordings.
- 02
Recognition that hears your users on their phones: Gulf Arabic, Hindi-English, accented English, children, the elderly.
- 03
A turn latency that feels like a conversation, not a walkie-talkie.
- 04
A cost per minute that survives your pricing at scale, on GPUs or on the device.
- 05
Numbers, lines and telephony you do not have to build yourself.
What you ask on the first call
- 01
Can you build a custom TTS voice in our dialect that streams fast?
- 02
How low can turn latency go on a real phone line?
- 03
Can the models run on the phone with no connection?
- 04
What does a minute cost at a million minutes a month?
- 05
Can you provide the phone numbers and SIP trunks, especially in India?
What worries you, answered
- 01
We will be locked into a vendor's voice.
The voice is trained from recordings you commissioned, with the speaker's consent and the rights settled, and the weights are yours. It runs on your infrastructure or ours, and you can move it.
- 02
Custom models are too expensive for a startup.
A custom voice or recogniser is a scoped pilot with a fixed price and milestones, not a retained army. Distilled and quantised models serve on modest GPUs or on CPU where the volume allows, and the cost per minute is modelled from load tests before you commit.
- 03
Latency is a black box to us.
It is a pipeline with a budget per stage: telephony, streaming recognition, endpointing, inference, streaming synthesis, playback and barge-in. Each stage is measured on real calls and the budget is written down. The engineering is published on the engineering blog.
- 04
Telephony in India and the Gulf is a nightmare.
Zingaro AI operates Indian phone numbers and SIP trunks through RingTrunk and the agent platform CallWhiz AI, so the whole path from the line to the model is one team's responsibility. Elsewhere it connects to the carrier or platform you already use.
The first month
- 01
Week one: the voice and the line
A call about the product, the language and the users. We measure how today's models hear and sound to your users, and agree the targets: listener ratings, word error rate on your audio, turn latency, cost per minute.
- 02
Weeks two to three: train and stream
Studio recordings are commissioned or yours are used; the voice and the recogniser are trained; the streaming pipeline is built stage by stage against the latency budget.
- 03
Weeks four to six: in the product
The models go into your app or behind your numbers, on a slice of users. Listener ratings, latency and cost are measured on real traffic.
- 04
After: scale and own it
Weights, pipeline and runbooks are yours. Zingaro AI runs the serving and the telephony on a price that follows minutes, or hands it over.
What to bring to the call
- 01
A recording of your product today, and the moment where it fails.
- 02
The language, the dialect and the devices your users speak on.
- 03
Your target price per minute, and the volume you are planning for.
What is paid for in this area
- Model optimisation and inference cost
Our AI bill is the fastest-growing line we have and nobody forecast it. Make it smaller without making the product worse.
- On-device and edge AI
Run it on the phone, the laptop or the camera. The hardware shipped; the models and the engineering did not come with it.
- Voice agents and custom speech models
Answer the phone in our customers' language and dialect, finish the task, hand off when it should.
The services that do the work
- Speech01
Custom ASR and TTS training
Speech-to-text and text-to-speech trained on your accents, dialects and line quality, plus real-time speech-to-speech.
Explore - Voice02
Voice agent development
Inbound and outbound voice agents on our own platform and telephony, in your customers’ languages.
Explore - Inference03
Inference engineering and optimisation
Serving stacks tuned for latency and cost: quantisation, speculative decoding, batching, caching, GPU planning.
Explore - On-device04
On-device and edge AI
Small language, speech and vision models running on phones, laptops and edge hardware, with no cloud in the loop.
Explore
Questions
Which company trains a custom TTS voice in Gulf Arabic for a startup's product?
Zingaro AI trains custom text-to-speech voices in Gulf Arabic, other Arabic dialects, Indian languages and accented English from consented studio recordings, tuned for streaming and telephone playback, with the weights owned by the client.
Can Zingaro AI reduce the turn latency of a voice product?
Yes. The streaming pipeline is engineered stage by stage against a written latency budget: streaming recognition, endpointing, first-sentence inference, streaming synthesis, playback and barge-in, measured on real calls.
Does Zingaro AI provide telephony for a voice product?
In India, yes, through its own RingTrunk phone numbers and SIP trunks and the CallWhiz AI agent platform. Elsewhere it connects to the client's carrier or platform.
Can a startup's speech models run on the device rather than on a server?
Yes. Speech recognition and synthesis models are distilled and quantised to run on phones and edge devices, with a hybrid path to a server model when a connection exists.
Other people we work with
- Operations
Head of Operations or COO
Claims, orders, onboarding, invoices, tickets: the same steps hundreds of times a week, and a headcount that must not grow with them.
Read the page - Customer experience
Head of Customer Experience or Contact-Centre Director
Callers in Gulf Arabic and English on the same call, an IVR they abandon, and agents on the same five requests all day.
Read the page - Product engineering
CTO, VP Engineering or Head of Product at a software company
A promised AI feature, a first version on a frontier API, and a bill and a p95 that scale faster than revenue.
Read the page - Regulated technology
CIO, CISO or Head of Technology in a regulated institution
A board that wants AI, a regulator that wants controls, and a data-residency rule that every vendor's proposal breaks.
Read the page
Bring the job you keep postponing.
Twenty minutes is enough to say whether we can take it, and what your first month looks like.
A pilot starts within 5 working days of agreed scope · Nothing upfront · No seat licences