Skill UI

Guides LangChain teams through a production deployment checklist covering security, resilience, observability, performance, testing, and cost controls so you can validate readiness before launch or audit live systems.

Deploys machine-learning anomaly detection across OT networks by modeling deterministic SCADA/Modbus/DNP3/OPC UA traffic, correlating with historians, and flagging behavior deviations, rogue devices, or process anomalies for industrial control security monitoring.

Builds NeMo Guardrails and custom Python validators to enforce input/output safety for LLM apps, blocking prompt injection, PII leaks, toxic outputs, hallucinations, and schema violations before they reach downstream systems.