Autonomous AI for Molecular Biology
Purpose-built, domain-trained, multi-agent system running entirely on your infrastructure. VigyanLLM is not a wrapper around existing APIs — it is a sovereign biomedical AI platform with a proprietary inference engine, 46 batches of curated training data, and a dedicated verification agent.
📊 320,000+ Purpose-Built Records
46 specialized training batches — each targeting a precise biological subdomain. Batch 19: 50,000 clinical reasoning records. Batch 20: 50,000 genomic design records. Batch 46: 110,025 CRISPR structural anomaly records processed on dedicated AWS GPU infrastructure. Not scraped. Not generic.
🔐 No External API. Ever.
VigyanLLM pipelines run on secure cloud infrastructure, combining Primer3 thermodynamics, SantaLucia nearest-neighbour calculations, AutoDock Vina physics-based scoring, and GNINA CNN rescoring. No OpenAI, Anthropic, or Cohere APIs are used. Your data stays sovereign.
✅ Pipeline Validation Layer
A single LLM cannot check its own hallucinations. VigyanLLM's ChinhAI agent is a dedicated verification layer — cross-checking primer off-target binding, validating molecular docking energetics, and flagging sgRNA instability before any output reaches you.
Three Agents. One Research Pipeline.
Core — Orchestration Layer
Parses research intent, decomposes complex biological queries, and routes sub-tasks. Synthesizes outputs into a coherent final report.
SubBrain — Domain Reasoning
The specialist. Handles biological knowledge retrieval, sequence analysis, protein prediction, and pathway mapping.
ChinhAI — Verification Gate
The validation layer. Cross-checks results against off-target databases and physics-based benchmarks before release. No single model has the final word.