ARCHITECTURE

Multi-Agent System Architecture

VigyanLLM is built on a three-agent architecture designed for sovereign biomedical AI. Each agent has a distinct responsibility, and outputs flow sequentially through orchestration, domain reasoning, and verification before reaching the researcher.

STEP 1

Agent 01 — Core Orchestration

Parses research intent, decomposes complex biological queries into sub-tasks, routes work to the appropriate specialist, and synthesizes outputs into a coherent final report. The orchestration layer ensures every request is handled systematically.

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STEP 2

Agent 02 — SubBrain Domain Reasoning

The domain specialist. Handles biological knowledge retrieval, sequence analysis, protein structure prediction, molecular pathway mapping, and clinical reasoning using 320,000+ purpose-built biomedical records across 46 specialized training batches.

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STEP 3

Agent 03 — ChinhAI Verification

The validation gate. Cross-checks every output against physics-based benchmarks, off-target databases, and thermodynamic models before release. No single model has the final word — every result is verified before the researcher sees it.

Platform Capabilities

🧬 Primer & PCR Design

Automated design with 24-step thermodynamics validation, BLAST specificity checking, and off-target screening for laboratory protocols.

🔬 Protein Structure

Predict accurate 3D protein conformations and identify structural anomalies for drug target discovery using AlphaFold, RosettaFold, and ESMFold.

💊 Molecular Docking

GPU-accelerated docking with realistic binding energy calculations and interaction surface mapping. Vina-GPU with -8.5 kcal/mol benchmarks.

📊 Gene Expression

RNA-Seq analysis and pathway integration for complete systems biology understanding using DESeq2, edgeR, KEGG, and Reactome.

✂️ CRISPR Analysis

sgRNA-DNA heteroduplex instability analysis and PAM variation mapping for precise genome editing with HNH domain validation.

🏥 Clinical Reasoning

Differential diagnosis and symptom mapping trained on 50,000 dedicated clinical reasoning records for research-grade clinical support.

VigyanInferenceEngine: All capabilities run on the proprietary VigyanInferenceEngine — a native GGUF inference engine with zero external API dependency. Every inference is processed on secure AWS infrastructure or dedicated on-premises hardware. Your data never leaves your infrastructure.
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