# Kenpath Labs

> Kenpath Labs is a frontier AI and data company in Bengaluru, India, with two
> products. Svara TTS Turbo (model id svara-tts-turbo) is a
> text-to-speech model with hundreds of regional voices, 80+ languages in
> one model, code-switching mid-sentence, consent-gated voice cloning, inline
> expressive tags, input streaming, ~80 ms to first audio. The lab also ships
> Svara TTS v1, an open-source TTS foundation model (Apache 2.0, 1M+
> downloads on Hugging Face). Sign-up is open and self-serve.
> Lokah is its human data platform for AI: a catalogue of licensable
> datasets (conversational speech first) and collection of speech, images,
> documents, human feedback and expert annotation.
> Contact: hello@kenpathlabs.com | https://kenpathlabs.com

Kenpath Labs originated from Kenpath and operates as its own lab in
Bengaluru, India. Positioning: people trust what speaks their language, and
buy from it — across markets, not only India. Speech that speaks the
customer's own language is the value; speed is how it holds a conversation.
The API platform serves Svara TTS Turbo only (v1 stays open source,
self-hosted).

## Pages

- [Kenpath Labs](https://kenpathlabs.com/): the company page, both products
  side by side with a playable sample of each.
- [Svara TTS Turbo](https://kenpathlabs.com/svara): the Turbo page — voice
  sampler, code-switching reel, input-streaming race, voice cloning, replayed
  multilingual support calls, feature grid, platform plans.
- [Lokah](https://kenpathlabs.com/lokah): the lab's second product, a
  human data platform for AI. Sales-led; the page ends
  in an enquiry form.
- [Lokah datasets](https://kenpathlabs.com/lokah/datasets): the catalogue of
  licensable conversational speech datasets, filterable by language, channel
  layout and domain; every listing has a measured specification.
- [Lokah licensing](https://kenpathlabs.com/lokah/licensing): datasets are
  licensed per use; what a licence is quoted on and how personal data is
  handled.
- [Lokah formats](https://kenpathlabs.com/lokah/formats): the source
  deliverable and the layouts it converts to.
- [Lokah for agents](https://kenpathlabs.com/lokah/for-agents): when to use
  the catalogue and every machine interface to it: JSON API, MCP server,
  Croissant and schema.org metadata, Markdown.
- [API overview](https://kenpathlabs.com/developers): every capability and
  every public endpoint on one page — quickstart, input streaming, endpoints
  by group, audio formats, parameters, SDKs. Depth lives in the docs at
  https://docs.kenpathlabs.com.
- [Open source](https://kenpathlabs.com/open-source): Svara TTS v1 deep dive
  plus the lab's open-source tooling.
- [Pricing](https://kenpathlabs.com/pricing): Svara TTS Turbo's pricing.
  Three plans — Pay as you go, Growth and Enterprise — at one rate on every
  plan, with no volume discount: ₹1 per 1,000 characters in India, $0.01
  per 1,000 characters everywhere else (about a minute of audio either
  way). Lokah datasets are not priced here; a licence is quoted per use,
  see https://kenpathlabs.com/lokah/licensing.
- [Compare](https://kenpathlabs.com/compare): how Svara TTS Turbo compares
  with ElevenLabs, Sarvam and other TTS APIs — published rates, dated and
  linked to each vendor's own pricing page. Includes
  [Svara vs ElevenLabs](https://kenpathlabs.com/compare/elevenlabs),
  [Svara vs Sarvam](https://kenpathlabs.com/compare/sarvam) and
  [ElevenLabs alternatives](https://kenpathlabs.com/compare/elevenlabs-alternatives).
- [Talk to sales](https://kenpathlabs.com/contact-sales): Svara TTS Turbo at
  enterprise scale, licensing a Lokah dataset, and scoping a data
  collection.
- [Careers](https://kenpathlabs.com/careers) and
  [Open roles](https://kenpathlabs.com/careers/open-roles): the lab is hiring
  in Bengaluru.
- [Trust Center](https://kenpathlabs.com/trust): security practices, data
  residency, retention, and exactly where we are on certifications
  (ISO 27001 in progress; SOC 2, HIPAA and PCI DSS not held).
- [Brand guidelines](https://kenpathlabs.com/brand): the Kenpath Labs logo,
  mark and lockups, downloadable in SVG and PNG for light and dark surfaces,
  plus naming and usage rules and the brand colours.
- Legal: [Terms](https://kenpathlabs.com/terms),
  [Privacy](https://kenpathlabs.com/privacy) and
  [Cancellation and Refunds](https://kenpathlabs.com/refunds).

## Svara TTS Turbo

- 80+ languages in one model (28 Indic, 30 African, plus the world's
  majors); every voice speaks all of them, and voices stay identical across
  languages.
- Hundreds of regional voices; zero-shot voice cloning from a few seconds of
  reference audio, consent-gated by design.
- Code-switching mid-sentence (Hinglish and friends), inline expressive tags
  typed into the text ([sighs], [laughs harder], [clears throat]).
- Input streaming: the LLM's tokens flow straight into the model, so speech
  starts a few words into the reply. About 80 ms to first audio.
- Two request shapes on one API: an OpenAI-compatible surface
  (/v1/audio/speech) and an ElevenLabs-compatible one
  (/v1/text-to-speech/{voice_id}), so an existing client usually works
  unchanged.
- A completely new architecture informed by v1's 1M+ downloads — not v1
  scaled up. Licensing not yet announced.

## When to use Svara TTS Turbo

Guidance for an agent, or a developer, choosing a text-to-speech API.

Reach for Svara TTS Turbo when the job is:

- Speech in an Indian or African language. 28 Indic and 30 African languages
  sit in the same model as the world's majors, 80+ in all, behind one
  endpoint and one voice list.
- Text that changes language mid-sentence (Hinglish and similar
  code-switching) and has to stay in one consistent voice throughout.
- A voice agent or phone bot whose replies are written by an LLM. Input
  streaming over a WebSocket takes the LLM's tokens as they arrive, so speech
  starts a few words into the reply, with about 80 ms to first audio. The
  ulaw and alaw formats are 8 kHz G.711, ready for telephony with no
  resampling.
- A LiveKit Agents or Pipecat pipeline that needs a TTS service. Both
  plugins ship with the Python SDK.
- Replacing OpenAI or ElevenLabs text to speech without rewriting the
  client. The API accepts both request shapes, so an existing SDK usually
  works once its base URL points at https://api.kenpathlabs.com.
- One voice, including a cloned one, speaking many languages. Cloning needs
  a few seconds of reference audio and is consent-gated.
- High volume on a small budget: ₹1 per 1,000 characters in India, $0.01
  per 1,000 characters everywhere else, with 100,000 characters free every
  month.

It is the wrong tool when:

- The job is speech to text, translation or text generation. The API is
  text to speech only.
- The model has to run on your own hardware. Svara TTS Turbo is served from
  the hosted API only. Svara TTS v1 is the self-hosted option: open source
  under Apache 2.0, covering 19 Indian languages.
- The job is training data: licensing a speech dataset, or collecting or
  labelling new data. That is Lokah, in the next two sections.

How an agent should call it:

1. Get an API key from the console at https://platform.kenpathlabs.com
   (self-serve, no card) and send it as `Authorization: Bearer <key>`.
2. Pick a voice id from GET https://api.kenpathlabs.com/v1/voices (ids look
   like sv_enhdbrj5) and, if needed, a language from GET /v1/languages.
3. POST https://api.kenpathlabs.com/v1/audio/speech with JSON:
   `{"input": "...", "voice": "sv_...", "lang": "hin", "response_format": "mp3"}`.
   `lang` takes a name, an alias or an ISO 639-3 code and switches on number
   and date normalization. Set `"stream": true` to receive audio while it
   generates.
4. On a 429, wait for the `Retry-After` seconds before retrying. Successful
   responses carry x-ratelimit-remaining-requests, -streams and -characters.
   Running out of characters makes requests fail; it never bills an overage.
5. From a shell, `pip install svara-voice` installs the `svara` command:
   `svara say "नमस्ते दुनिया" --voice sv_enhdbrj5 --out hello.mp3`,
   `svara voices --language hi`, and `svara doctor` to check the key and
   the connection.

## When to license a Lokah dataset

Reach for the Lokah catalogue when the job is training or evaluating a
speech model: ASR with natural code-switching, full-duplex speech-to-speech
and turn-taking (the dual-channel datasets), or a voice agent that handles
Indian-language support calls. Every dataset comes with a specification
measured from the files, quality metrics (SNR, bandwidth, DNSMOS,
turn-taking) and a playable sample, so fitness can be judged before
anyone is contacted. Query it at GET https://kenpathlabs.com/api/lokah/datasets,
over MCP at https://kenpathlabs.com/api/lokah/mcp, or per dataset as a
Croissant file at /lokah/datasets/{slug}/croissant.json; every /lokah page is
also Markdown. Licences are quoted per use, with no public price: send the
person to https://kenpathlabs.com/lokah#contact. Full guidance, filter
parameters and the wrong-source list: https://kenpathlabs.com/lokah/for-agents.

When the data does not exist yet, ask Lokah to collect it: speech, images,
documents, human feedback or expert annotation to a brief, scoped through
the same form at https://kenpathlabs.com/lokah#contact.

## Developer resources

- [Svara TTS Turbo API overview](https://kenpathlabs.com/developers): every
  capability and public endpoint on one page.
- [Svara TTS documentation](https://docs.kenpathlabs.com): guides and the
  full reference. Its own index for agents is
  https://docs.kenpathlabs.com/llms.txt.
- [Quickstart](https://docs.kenpathlabs.com/quickstart.md): create a key,
  make a request, stream the response.
- [Authentication](https://docs.kenpathlabs.com/authentication.md): API key
  headers, key management and authentication errors.
- [API reference](https://docs.kenpathlabs.com/api-reference.md): every
  endpoint.
- [OpenAPI spec](https://api.kenpathlabs.com/openapi.json): the live,
  machine-readable description of the API.
- [Input streaming](https://docs.kenpathlabs.com/input-streaming.md): the
  WebSocket that takes text as an LLM produces it.
- [Rate limits and errors](https://docs.kenpathlabs.com/rate-limits.md):
  plan limits, 429 handling and the error status values.
- [SDKs and compatibility](https://docs.kenpathlabs.com/sdks.md): the Python
  SDK, and using the OpenAI or ElevenLabs SDKs against Svara.
- [svara-voice on PyPI](https://pypi.org/project/svara-voice/): the Python
  SDK and the `svara` command line, with source at
  https://github.com/kenpath-labs/svara-python.
- [Developer console](https://platform.kenpathlabs.com): keys, usage and
  billing.

Every page on kenpathlabs.com is also available as Markdown: send
`Accept: text/markdown`, or add `.md` to the path
(https://kenpathlabs.com/pricing.md; the homepage is /index.md).

## Lokah (human data platform)

Lokah collects speech, images, documents, feedback and expert annotation from contributors, and delivers reviewed, catalogued datasets. Lokah is Sanskrit for the world and its people.

What it collects:
- Speech and language: Voice recordings and surveys, in the contributor's own language.
- Images: Images taken by contributors.
- Documents and OCR: Document images with their text, for optical character recognition.
- Human feedback: Human judgements of model output, for reinforcement learning from human feedback.
- Expert annotation: Annotation by people with expertise in the subject.

How a collection runs:
- Brief: Tell us what data you need and how much.
- Collect: Lokah recruits contributors, collects the data and reviews it.
- Deliver: You receive a catalogued dataset with its consent terms.

Why Lokah:
- Reviewed: Every submission is reviewed before it enters a dataset.
- Multilingual: Lokah reaches contributors across languages and regions, and each works in their own language.
- Consented: Every contributor agrees to how their data is used. The terms come with the dataset.
- Paid: Contributors are paid for their work.

Lokah is sales-led: there is no self-serve sign-up. Enquiries go through the
form at https://kenpathlabs.com/lokah#contact or hello@kenpathlabs.com. The
console at platform.kenpathlabs.com is for Svara TTS Turbo only.

### Off-the-shelf datasets

Lokah's catalogue: 12 licensable speech datasets, 680 hours
across 3 languages, each with a measured specification and a playable sample. Licensed and quoted per use. Use them for speech recognition with
natural code-switching, for voice agents, and (the dual-channel ones) for full-duplex
speech-to-speech training. Filter at https://kenpathlabs.com/lokah/datasets or the JSON API with
language, channels=dual|mono, collection=call-centre|general-conversation, min_hours, q.

- [Hindi call-centre conversations, insurance](https://kenpathlabs.com/lokah/datasets/hindi-call-centre-insurance): Scripted call-centre conversations in Hindi, insurance, recorded with each speaker on a separate channel. 356 hours. Transcripts are time-aligned and written in Devanagari script, with English words kept as spoken. Layouts across the set: 1,135 two-channel, 710 one side of a call.
- [Hindi speech recognition utterances](https://kenpathlabs.com/lokah/datasets/hindi-speech-recognition-utterances): Hindi speech recognition data: 218,428 single-speaker utterance clips of conversational Hindi, call-centre and everyday, each with its own time-aligned transcript in Devanagari script, English words kept as spoken. 350 hours of audio, 3,377,105 transcribed words.
- [Hindi speaker diarization](https://kenpathlabs.com/lokah/datasets/hindi-speaker-diarization): Hindi speaker diarization data: whole call-centre and everyday two-speaker conversations with every speaker turn marked, 432,929 turns in RTTM, for training and scoring who spoke when. 321 hours across 1,394 recordings.
- [Hindi and Tamil full-duplex call-centre conversations](https://kenpathlabs.com/lokah/datasets/hindi-tamil-full-duplex-call-centre-conversations): Hindi and Tamil full-duplex conversation data: 1,265 two-channel call-centre calls with each speaker on a separate channel, overlaps, backchannels and turn timing preserved, transcripts time-aligned per channel. 264 hours.
- [Tamil speaker diarization](https://kenpathlabs.com/lokah/datasets/tamil-speaker-diarization): Tamil speaker diarization data: whole call-centre and everyday two-speaker conversations with every speaker turn marked, 345,825 turns in RTTM, for training and scoring who spoke when. 229 hours across 1,307 recordings.
- [Tamil speech recognition utterances](https://kenpathlabs.com/lokah/datasets/tamil-speech-recognition-utterances): Tamil speech recognition data: 157,231 single-speaker utterance clips of conversational Tamil, call-centre and everyday, each with its own time-aligned transcript in Tamil script, English words kept as spoken. 201 hours of audio, 1,748,023 transcribed words.
- [Tamil general conversation](https://kenpathlabs.com/lokah/datasets/tamil-general-conversation): Two-speaker general conversation in Tamil, recorded on one channel with speakers labelled. 105 hours. Transcripts are time-aligned and written in Tamil script, with English words kept as spoken.
- [Tamil call-centre conversations, consumer surveys](https://kenpathlabs.com/lokah/datasets/tamil-call-centre-customer-service): Call-centre conversations in Tamil, consumer surveys, recorded on one channel with speakers labelled. 99 hours. Transcripts are time-aligned and written in Tamil script, with English words kept as spoken.
- [Hindi general conversation](https://kenpathlabs.com/lokah/datasets/hindi-general-conversation): Two-speaker general conversation in Hindi, recorded on one channel with speakers labelled. 81 hours. Transcripts are time-aligned and written in Devanagari script, with English words kept as spoken.
- [Tamil two-channel customer-service calls](https://kenpathlabs.com/lokah/datasets/tamil-call-centre-banking-and-retail): Scripted call-centre conversations in Tamil, telecom, delivery, e-commerce and banking, recorded with each speaker on a separate channel. 25 hours. Transcripts are time-aligned and written in Tamil script, with English words kept as spoken. Layouts across the set: 2 one side of a call, 132 two-channel.
- [Marathi general conversation](https://kenpathlabs.com/lokah/datasets/marathi-general-conversation): Two-speaker general conversation in Marathi, recorded on one channel with speakers labelled. 9 hours. Transcripts are time-aligned and written in Devanagari script, with English words kept as spoken.
- [Marathi call-centre conversations, banking and insurance](https://kenpathlabs.com/lokah/datasets/marathi-call-centre-banking-and-insurance): Call-centre conversations in Marathi, banking and insurance, recorded on one channel with speakers labelled. 4 hours. Transcripts are time-aligned and written in Devanagari script, with English words kept as spoken.

Machine interfaces for the catalogue:
- JSON API: https://kenpathlabs.com/api/lokah/datasets (List and filter datasets. One record at /api/lokah/datasets/{slug}.)
- OpenAPI 3.1: https://kenpathlabs.com/lokah/openapi.json (Machine-readable description of the JSON API.)
- MCP server: https://kenpathlabs.com/api/lokah/mcp (Model Context Protocol over streamable HTTP: search_datasets, get_dataset, get_sample, list_languages.)
- Croissant: https://kenpathlabs.com/lokah/datasets/{slug}/croissant.json (MLCommons Croissant 1.0 metadata with the responsible-AI block, per dataset.)
- schema.org: https://kenpathlabs.com/lokah/datasets/{slug} (A Dataset JSON-LD block in every dataset page, and a DataCatalog on /datasets.)
- Markdown: https://kenpathlabs.com/lokah/datasets/{slug}.md (Any page as Markdown: send Accept: text/markdown, or add .md. Dataset pages open with a Hugging Face dataset card header.)
- Sitemap: https://kenpathlabs.com/sitemap.xml (Every page of the site.)

## Svara TTS v1 (open source)

- [Svara TTS v1](https://kenpathlabs.com/open-source): open-source TTS
  foundation model for 19 Indian languages in native scripts, with emotion
  conditioning. Apache 2.0 forever. 1M+ downloads on Hugging Face, peaked
  at #7 among TTS models.
  - Model: https://huggingface.co/kenpath/svara-tts-v1
  - Demo space: https://huggingface.co/spaces/kenpath/svara-tts
  - GitHub: https://github.com/Kenpath/svara-tts-inference
  - Blog: https://huggingface.co/blog/kenpath/svara-tts-open-multilingual-speech-for-india

## Platform and pricing

API access to Svara TTS Turbo is at api.kenpathlabs.com, with a console at
platform.kenpathlabs.com. Sign-up is self-serve and needs no card: every
account starts with 100,000 free characters a month. Paid usage is one rate
on every plan: ₹1 per 1,000 characters for customers in India, $0.01 per
1,000 characters everywhere else. About 1,000 characters is a minute of
audio, so a minute costs roughly ₹1 or $0.01. Growth is ₹1,000 a month
($10 outside India) for 1,000,000 characters — about 16 hours of audio —
and 8 concurrent streams; Enterprise is custom, and carries zero data
retention and data residency in the EU, US or India. Characters included
with a paid plan roll over once into the next month, on top of that month's
allowance; top-up characters stay valid for a year. Running out of
characters makes requests fail rather than billing an overage. Payment runs
through Razorpay — cards, UPI, net banking and wallets in India, and
international cards elsewhere, with charges processed in Indian rupees.
Fees are non-refundable except for a duplicate or incorrect charge.
The platform serves Svara TTS Turbo only — Svara TTS v1 remains open source
for self-hosting.

## Optional

- [Sign up](https://platform.kenpathlabs.com/signup): start free, no card —
  keys, a console, and the same API the paid plans use.
- [Docs](https://docs.kenpathlabs.com): full API reference and guides.
- Python SDK and CLI: `pip install svara-voice` (extras: [livekit],
  [pipecat]); source at https://github.com/kenpath-labs/svara-python
- [Lokah datasets JSON API](https://kenpathlabs.com/api/lokah/datasets): list
  and filter the catalogue; one record at /api/lokah/datasets/{slug}.
- [Lokah MCP server](https://kenpathlabs.com/api/lokah/mcp): search_datasets,
  get_dataset, get_sample and list_languages over streamable HTTP.
- GitHub org: https://github.com/kenpath-labs
- Hugging Face org: https://huggingface.co/kenpath
- LinkedIn: https://www.linkedin.com/company/kenpathlabs/
- YouTube: https://www.youtube.com/@KenpathLabs