BioLLM builds open-source large language models, fine-tuned for Indian biotech and deployed entirely on-premise. No patient genomics, no proprietary research, no sensitive data ever sent to the cloud.
Four purpose-built modules across research, diagnostics, pharma regulation, and crop genomics — grounded by retrieval that cites every answer.
There's a fundamental gap between the volume of biological data India generates and the tools available to process it. Generic AI can't speak the language of biology, and cloud AI isn't allowed near the data.
Scientists spend 60–70% of their time reading papers instead of doing research.
A genetic report takes days to summarize by hand; under 800 genetic counsellors nationwide.
A single CDSCO submission means weeks of repetitive documentation and lakhs in cost.
Crop scientists generate genomic data faster than they can extract insight from it.
Open-source LLMs — LLaMA 3, BioGPT, ESM-2 — fine-tuned on Indian biomedical data and grounded by a retrieval pipeline that cites every answer. Adopt one module or the full suite.
Query 35M+ papers in plain English and get synthesized, cited answers in seconds — with contradiction flags and a private internal knowledge base.
Turn a 20-page genetic test report into clear patient summaries and structured clinical reports — in under 30 seconds, across Indian languages.
Draft CDSCO-compliant submission documents in days, not weeks — with template intelligence and an automatic compliance checker.
Analyze crop genomics and identify desirable traits through natural language — no coding — to accelerate breeding programs.
Three principles shape every deployment — built so the most sensitive data in Indian science can finally meet modern AI without ever leaving the building.
On-premise or private-cloud deployment. Zero data leakage. Compliant with the DPDP Act 2023 by design — sovereignty isn't a setting, it's the architecture.
Open-source models fine-tuned (LoRA/PEFT) on Indian biomedical, regulatory and crop data. Retrieval grounds every answer in cited sources — not hallucinations.
Adopt one module or the whole platform. Kubernetes-based, scaling from a single lab to 10,000+ users, with REST, FHIR and HL7 integration.
India's biotech sector crossed ₹10.8 lakh crore in 2024, growing 14–16% a year — yet AI adoption sits under 8%. The awareness exists; the solutions don't.
Run a free 30-day pilot of any module on your own infrastructure. See domain AI work on your data — without your data ever leaving your servers.