I will build evaluations and observability for your rag or ai agent

Your AI agent works. But is it accurate, reliable, fast, and getting better instead of worse?

I build automated evaluation and observability systems for RAG applications, AI agents, and production LLM workflows.

Depending on your stack, I can help evaluate and monitor:

• Faithfulness and hallucinations
• Answer relevance
• Retrieval and RAG quality
• Citation accuracy
• Agent task completion
• Tool usage
• Memory recall
• Latency and failures
• Regression between releases
• Production anomalies

I can also integrate evaluation into CI/CD so changes are automatically tested before reaching production.

My own AI systems include automated RAG evaluation, ML anomaly detection, hallucination scoring, cloud observability, and production monitoring across AWS, Azure, GCP, Microsoft Fabric, Databricks, and Snowflake.

Please contact me before ordering so I can understand your architecture and recommend the right scope.