Insights, research, and deep dives from India's sovereign AI lab. Technical explainers, industry analysis, product updates, and the story of building frontier AI from Jaipur.
GPT-4 can write Hindi, but can it understand Hinglish in a BFSI context, navigate Indian jurisprudence, or process a Rajasthani dialect IVR call? We explain why fine-tuning on English base models is the wrong strategy for India's AI future — and what Krishna LLM is doing differently.
Read Article →10,000 hours of Indian audio — news, IVR calls, field recordings. Full accuracy numbers across all 22 scheduled languages plus Hinglish.
GPT-4 can write Hindi, but can it understand Hinglish in a BFSI context, navigate Indian jurisprudence, or process a Rajasthani dialect IVR call? We explain why fine-tuning on English base models is the wrong strategy for India's AI future — and what Krishna LLM is doing differently.
India's Digital Personal Data Protection Act is now in force. Plain-English breakdown of implications for enterprises using speech AI and LLMs — and what you need to do.
We deployed a rice blast disease detection model on a Raspberry Pi-class device achieving 94.8% accuracy at 38ms inference. Full technical walkthrough and bill of materials.
Hinglish, Tanglish, Banglish — code-mixed languages are how hundreds of millions of Indians communicate online. Why every multilingual model still struggles with them.
The industry bills you per character, per token, or per second. Here's the thinking behind EngineAI's flat ₹5/engagement hour model and why it aligns better with enterprise ROI.
How we built voice cloning that works on Indian accents without a professional recording studio. Technical walkthrough of our few-shot speaker adaptation architecture.
Case study: 200-seat contact centre, 12,000 calls per day, Hinglish and Bhojpuri mix. Migration from Google STT, the process, and month-1 results.
Why building AI on foreign cloud infrastructure is a strategic risk for Indian enterprises, and what AI sovereignty actually means in practice for data, compute, and model ownership.
Twice a month: research summaries, product updates, and the honest take on what's actually happening in Indian AI — no fluff, no hype.