Complete SDK documentation and REST API reference for Fiddler AI Observability Platform.

Hands-on quick start guides for evaluating LLM applications, testing with custom LLM-as-a-Judge metrics, and comparing model outputs using Fiddler Evals.

# Fiddler Query Language ## Overview [Custom Metrics](https://docs.fiddler.ai/observability/platform/custom-metrics) and …

Master LLM and AI application experiments with comprehensive tutorials covering the Fiddler Evals SDK, custom evaluators, model comparison, and custom experiment creation.

# LLM Evaluation Prompt Specs ## The Challenge With LLM Evaluation When building production LLM applications, evaluation is critical, but it's often the most time-consuming bottleneck in your …

Advanced guide to Fiddler's LLM-as-a-Judge capabilities, including custom prompting, model selection, performance optimization, and enterprise deployment patterns.

The future of AI is agentic—autonomous systems that reason, plan, and coordinate across multiple agents to solve complex problems. Fiddler Observability is built for this future, providing …

# Evaluations Building reliable AI applications requires systematic evaluation to ensure quality, safety, and consistent performance. This section provides ...

Advanced experiment patterns for production LLM applications including multi-score evaluators, complex parameter mapping, and comprehensive experiment analysis.

# Simple LLM Monitoring This guide will walk you through the basic onboarding steps required to use Fiddler for monitoring of LLM applications, **using sample data ...