LLM Guardian — Production-Grade Observability & Safety for Large Language Models

Description

LLM Guardian is an end-to-end observability and safety monitoring platform designed for production LLM applications. As large language models move from experimentation to real-world deployment, traditional observability tools fall short. LLM Guardian fills this gap by capturing LLM-specific telemetry and turning it into actionable insights and incidents. What LLM Guardian Does: -Tracks latency, token usage, cost, and errors -Detects PII exposure and hallucination risk -Applies monitoring rules to flag abnormal behaviour -Automatically generates severity-based incidents -Visualizes LLM health through a clean, real-time dashboard -Integrates with Datadog for monitoring and alerting How it was built: Frontend: Next.js, React, Tailwind CSS, Recharts Backend: Next.js API Routes, Node.js Database: Supabase PostgreSQL ORM: Prisma AI: Google Cloud AI (Gemini / Vertex AI) Observability: Datadog Deployment: Vercel LLM Guardian brings the same operational rigour used for mission-critical cloud systems to AI applications, making LLM behaviour transparent, measurable, and reliable. LLM Guardian helps teams identify issues before users are impacted, reduce operational risk, and confidently run LLMs in production.