Evaluation patterns, release gates, and anti-hallucination techniques for developer-focused AI workflows.
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Updated
Mar 27, 2026 - Python
Evaluation patterns, release gates, and anti-hallucination techniques for developer-focused AI workflows.
Single-agent, evidence-grounded claim verification to catch LLM hallucinations — a pluggable fact-gate for agent-arena and any multi-agent system (CrewAI, AutoGen, LangGraph).
Provider-agnostic enterprise RAG and agent evaluation harness for Azure Foundry, vLLM, Ollama, and local demos.
RAG evaluation workbench for retrieval recall, citation coverage, groundedness checks, and failure analysis
Retrieval-Augmented Generation (RAG) research application with groundedness evaluation to increase reliability and confidence in LLM generated output (post-hoc hallucination detection).
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