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Whitepaper

The State of Indic LLM Data 2026 (whitepaper)

A field report on data gaps, model failure modes, and what production-grade Indic and low-resource language data looks like.

Illustration representing multilingual Indic language coverage

This whitepaper maps the state of training data for India's languages in 2026: where the gaps are, how they show up as model failures, and what rights-cleared, production-grade data actually looks like. It draws on our work building proprietary multilingual datasets across 400 languages.

Inside: the low-resource data gap quantified, common failure modes in deployed Indic models, a procurement checklist for provenance and consent, and how to scope a custom collection.

About this report

What's in the whitepaper

Is the whitepaper gated?

Yes — submit your email and we'll send the download link. No marketing follow-up unless you opt in.

Who is it for?

AI labs, enterprise ML teams and procurement leads evaluating Indic and low-resource language data.

Need data like this?

License a proprietary dataset, or commission a collection in the languages you need.