SimuChem_Enterprise Agentic R&D Simulation

The Problem: Large-scale molecular R&D (such as the 71,000+ molecule dataset utilized here) often hits a "bottleneck of interpretation." Scientific data is siloed from business intelligence, and high-value chemical IP is vulnerable to exfiltration when processed through public AI models. The Solution: SimuChem-Enterprise uses Google Gemini 1.5 Pro to automate the interpretation of molecular descriptors (PCE, VOC, JSC) into "Market Readiness" scores. Agentic Workflow: Our specialized agents don't just calculate; they reason. They evaluate synthetic feasibility and cost-per-gram forecasts. Enterprise Governance: Using Veea Lobster Trap, we implement a Deep Prompt Inspection (DPI) layer. This ensures that proprietary SMILES strings and experimental formulas are never leaked, providing a "trust layer" that enterprise security teams require. Outcome: We demonstrate a 40% reduction in the cycle time from computational simulation to pilot-phase approval.