Contextual AI Blog

Why Diagnostic Metrics Matter for Agent Evaluations at Scale

Traditional AI evaluations fail at scale, providing only pass/fail metrics without revealing why models break or what to fix across thousands of test cases. LMUnit solves this with a diagnostic evaluation system that identifies specific failure patterns and introduces the WeightedLMUnitScore metric, enabling teams to pinpoint and prioritize improvements efficiently when testing AI models at enterprise scale.

User feedback and annotation is now built into the Contextual AI Platform

Contextual AI Summer Product Updates

Contextual AI Announces Strategic Partnerships with Leading RSIs to Accelerate Enterprise AI Adoption

Context Engineering for your MCP Client

Open-Sourcing the Best Local Text-to-SQL System

Contextual AI’s State-of-the-Art Reranker Coming to Snowflake Cortex AI

Introducing the Document Parser for RAG

What is RAG? A Definitive Guide for Enterprise AI