Human data designed around your model, not a public catalogue.
Sonexis works with AI teams that need realistic, consented, structured voice data for training, fine-tuning, evaluation, and benchmarking.
Teams building with speech and conversational AI.
Data types designed for AI workflows.
Custom conversational voice datasets
Multi-speaker conversations built around your specific deployment scenario, language mix, and speaker profile.
Evaluation datasets
Data structured to test model performance against real speech behaviour, not idealised conditions.
Benchmark datasets
Standardised evaluation sets for ASR, TTS, and conversational AI benchmarking across languages.
Managed collection programmes
Ongoing collection designed, managed, and delivered by Sonexis for teams with continuous data needs.
Ongoing data pipelines
Repeatable, scheduled collection workflows across languages, scenarios, and speaker profiles.
QA and metadata-ready delivery
Every delivery includes consent records, language tags, speaker metadata, QA notes, and a format agreed in advance.
Buyer-specific collection from scope to delivery.
Each dataset starts from your model and use case, not from a generic template. We scope the collection around your requirements, manage the contributor workflow, review submissions, and deliver structured data.
See the full processYou share the model and use case
Deployment environment, expected failure modes, language requirements.
We map language and speaker requirements
Code-switched combinations, regional accents, multi-speaker structure.
We define conversation scenarios
Task design, expected behaviour patterns, and edge cases.
Contributor tasks are assigned through Collect
Screened contributors receive structured tasks with clear guidelines.
Submissions go through QA review
Audio quality, language match, consent status, task accuracy.
Dataset is delivered in agreed format
Structured delivery with metadata, manifests, and QA notes.
Feedback improves the next batch
Iteration based on model performance and data quality review.
Built for serious data requirements.
Realistic speech behaviour
Interruptions, accents, code switching, informal phrasing.
India and multilingual focus
Indian English, Hindi, Hinglish, Punjabi, Marwadi, code-switched.
Consent-first workflows
Contributor consent tracked and tied to every submission.
Structured metadata
Speaker profile, language tags, scenario context, QA status.
QA-reviewed submissions
Audio quality, task accuracy, language match, usability checks.
Demand-led collection
Every dataset starts from your requirements, not from stock inventory.
Delivery-ready data
Structured output that fits training, evaluation, or benchmarking workflows.
Ongoing pipeline support
Repeatable collection for teams that need continuous data.
Start a dataset request.
Tell us what you are building and the languages you need. We will scope the right approach and respond with next steps.
Request Dataset Access