Voice AI

Voice models we develop. Voice systems we engineer.

Our own engineering

Smriti develops its own voice models and engineers the applications around them — the dialogue, business logic and integrations that make a voice system useful. Where a third-party speech service is the better fit, we integrate it.

Discuss an enterprise AI project See the pipeline

Illustrative 3D render of a voice system: incoming speech as a moving spectrogram, a voice model, and a spoken response waveform. — Illustrative 3D render

What we do

Our own models, and everything a voice system needs around them.

Speech is one part of a voice system. Understanding, dialogue, business logic and response all have to work with it — and each part has a clear owner.

Developed by Smriti

Voice-model development

We develop our own voice models, then refine and evaluate them for the application they will serve. They are Smriti's work — not a third-party service under another name.

Refinedfor the application's context and vocabulary
Evaluatedwith listening tests and task-level checks
Chosenfor a stage only when they suit it

Smriti engineers

Speech application engineering

The dialogue, context, business logic and integrations around speech, including the hand-off to a person when a conversation needs one.

Integrated where relevant

Third-party speech technologies

Cloud Speech-to-Text and Cloud Text-to-Speech from Google Cloud, integrated when they are the right choice for an application.

Voice pipeline

Where each stage can come from.

A spoken request passes through recognition, understanding, business logic, response and synthesis. At the two speech stages, the choice between our models and an integrated service is made per application.

Voice pipeline stages as columns, and the possible source for each stage as rows.
Audio in	Stage 1Speech recognitionSpeech to text	Stage 2Understanding and dialogueIntent, context, dialogue state	Stage 3Business logic and toolsRules, records, actions	Stage 4ResponseAnswer, action or hand-off	Stage 5Speech synthesisText to speech
Smriti voice modelsDeveloped by us, where suited	Smriti voice model	Not used at this stage	Not used at this stage	Not used at this stage	Smriti voice model
Integrated speech servicesGoogle Cloud, where relevant	Cloud Speech-to-Text	Not used at this stage	Not used at this stage	Not used at this stage	Cloud Text-to-Speech
Smriti application engineeringEvery stage	Channel and audio handling	Harness, context and dialogue logic	Workflow rules and integrations	Response rules and hand-off to a person	Voice selection for the application
Models selected per taskThird-party or our own	Not used at this stage	Language model, chosen per task	Not used at this stage	Language model, chosen per task	Not used at this stage

Audio out

Audio in

Stage 1
Speech recognition
Speech to text
- Smriti voice modelsSmriti voice model
- Integrated speech servicesCloud Speech-to-Text
- Smriti application engineeringChannel and audio handling
Stage 2
Understanding and dialogue
Intent, context, dialogue state
- Smriti application engineeringHarness, context and dialogue logic
- Models selected per taskLanguage model, chosen per task
Stage 3
Business logic and tools
Rules, records, actions
- Smriti application engineeringWorkflow rules and integrations
Stage 4
Response
Answer, action or hand-off
- Smriti application engineeringResponse rules and hand-off to a person
- Models selected per taskLanguage model, chosen per task
Stage 5
Speech synthesis
Text to speech
- Smriti voice modelsSmriti voice model
- Integrated speech servicesCloud Text-to-Speech
- Smriti application engineeringVoice selection for the application

Audio out

Smriti voice models
Integrated speech services
Smriti application engineering
Models selected per task

Where two sources are shown for a stage, one is chosen per application after evaluation — they are alternatives, not layers.

DrawingVoice pipeline — sources per stage

TypeSystem diagram

NoteVaries per application

Choosing per application

Our model or an integrated service?

We do not default to either. The decision is made for each application, against its own requirements.

What the application must say and hear
The languages, voices, vocabulary and speaking styles in scope, defined with the client.
Where it runs
The channel, its latency needs and any deployment constraints.
How data must be handled
What audio and text may be processed, stored or sent to an external service.
What evaluation shows
The option that performs better on the application's own tests is the one we use.

Evaluation

Evaluated by listening, and by doing the task.

We evaluate a voice system the way it will be used. Listening tests, against criteria agreed with the client, judge how it sounds. Task-level checks judge whether people get done what they came to do.

Language and voice coverage is defined per application and confirmed through evaluation. We do not claim support for every Indian language; we say what a system has been evaluated for.

Application: The service, the channel and the people who will use it
Languages and voices in scope: Defined per application. Each one is evaluated separately — nothing is assumed from another.
Listening tests: Structured sessions against agreed criteria: intelligibility, naturalness, and pronunciation of names and domain terms.
Task-level checks: Scripted scenarios: was the request understood, was the task completed, and did a hand-off to a person happen when it should?
Conditions: Audio channel, background noise and speaking styles the application must handle.
Known limitations: Recorded and shared with the client, not left out.
Outcome: Ready for the next stage, or refine and re-test

DrawingVoice evaluation record

TypeReporting format

NoteNo results shown

Capability overview

Smriti voice models and applications

Voice-enabled systems that combine Smriti's own voice-model development with speech applications and, where relevant, third-party speech services.

A capability overview describes what we engineer in this kind of project. It is not a case study: it names no customers and claims no results.

Voice AI

Need a system people can speak to?

Tell us who will use it, what they need to get done and the languages in scope. We will tell you what we would evaluate first.

Discuss an enterprise AI project Explore AI Harnesses