LaunchDarkly offers a runtime control platform that lets engineering teams manage feature flags, AI configurations, and experiments without redeploying code. The platform provides dynamic targeting, progressive rollouts, real‑time observability, and automatic rollbacks to ensure safe, rapid releases, while also supporting production experimentation with statistical analysis.
Funding
$200M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
7O+1Founders
Product
Problem
Software teams often struggle to release new features safely and quickly, facing risks such as performance regressions, errors, and the need for frequent redeployments to adjust behavior. Without real‑time visibility and control, incidents can reach customers before they are detected, leading to downtime and lost trust.
Solution
LaunchDarkly provides a runtime control platform that lets developers manage feature flags, AI configurations, and experiments without redeploying code. The system enables precise targeting and progressive rollouts, allowing features to be delivered to specific user segments or gradually increased in exposure. Real‑time observability monitors performance metrics, error rates, and latency, automatically triggering rollbacks when predefined thresholds are breached. Integrated debugging tools—including session replay, stack traces, and contextual flag data—help teams triage issues instantly. Experimentation capabilities let teams test variations in production, analyze engagement and behavior, and promote winning versions once statistical significance is reached, all through a unified web interface and SDKs.
Target Audience
Primary customers are engineering and product teams at SaaS, enterprise, and consumer software companies that need safe, rapid feature delivery and real‑time release risk management.
Features
- Feature flag management with dynamic targeting, segmentation, and progressive delivery
- AI config control for prompts, models, and agents without code changes
- Guarded releases that monitor custom performance thresholds and execute auto‑rollbacks in milliseconds
- Real‑time error monitoring, session replay, and stack‑trace correlation tied to each flag change
- Production experimentation with statistical analysis and automatic promotion of successful variations
- Scalable infrastructure handling over 45 trillion flag evaluations per day with sub‑200 ms latency worldwide
- Global network of 100+ points of presence ensuring low‑latency control across regions