Evals

If your customers depend on your AI to be right, your retrieval augmented generation pipeline is either earning trust or eroding it on every query. The difference often comes down to what you measure and how quickly you act on it. This guide shows you how to build a rigorous,

AI evaluation has shifted from static correctness checks to dynamic, context-aware judgment. As applications evolve beyond single-turn prompts into complex agents, tool use, and multi-step workflows, teams need evaluation that mirrors how users actually experience AI. Enter “LLM as a Judge” — using a model to evaluate other models or agents.

TL;DR Enterprise AI evaluation must cover three layers end to end: experiment, evaluate, and observe. Choose a platform that unifies offline evals, agent simulations, and online evals in production, and integrates with your observability stack. Priorities for 2025 include OpenTelemetry compatibility, human-in-the-loop pipelines, dataset curation from production logs, and

Evaluating AI agents requires more than a single score. Real systems involve multi-turn interactions, tool usage, retrieval, and branching decisions. The most reliable method is to measure quality at two layers: session level and node level. Session-level metrics summarize the outcome and user experience of a complete interaction. Node-level metrics

Introduction As artificial intelligence systems become more complex and increasingly agentic, the distinction between model evaluation and agent evaluation has become both critical and nuanced. While the evaluation of underlying models (such as large language models, LLMs) remains foundational, the rise of AI agents (autonomous entities capable of multi-step reasoning,

Large Language Models (LLMs) are at the heart of today’s AI systems, from chatbots and copilots to knowledge management tools. But deploying them successfully requires more than just good prompts or powerful models. Teams need to know: * Are outputs factually correct and safe? * Do they remain reliable across scenarios