LaunchDarkly Feature Management

A runtime control layer for software development and AI agent deployment that decouples code deployment from feature release, serving over 30 billion feature flag evaluations daily for enterprise customers including Paramount, Dior, and Savage X Fenty. The platform extends traditional feature flagging with AI-specific capabilities including LLM model distribution controls that route traffic across providers like OpenAI and Anthropic with cost tracking and toxicity scoring, agent observability dashboards that visualize tool satisfaction rates and reasoning chains, and custom judge evaluations for automated quality scoring. Development teams configure progressive rollouts with percentage-based targeting, automated rollback triggers based on error rate thresholds, and segment-based delivery rules using user attributes, device types, or custom context data. The experimentation module supports A/B and multivariate testing with multi-armed bandit optimization, holdout groups to prevent interference, and warehouse-native analysis that queries Snowflake, BigQuery, or Redshift directly without data duplication. Session replay captures user interactions for debugging failed experiments, while approval workflows enforce change management policies with role-based access control. The developer SDK covers 40-plus languages including Go, Python, Java, Swift, and React, with streaming architecture that propagates flag changes in under 200 milliseconds. An MCP server integrates with AI coding assistants for natural language flag management.