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Experimentation
LaunchDarkly + Snowflake: Introducing Warehouse Native Experimentation and Product Analytics
New: use Snowflake AI Data Cloud data to measure the impact of LaunchDarkly experiments.
Neha Julka picture
Neha Julka
Senior Product Marketing Manager, Solutions, LaunchDarkly
Risk mitigation
Introducing Guarded Releases: confidently innovate with safer, smarter software deployments
Industry Insights
LaunchDarkly Tops G2 Grid® for Feature Management in 2024: What You Need to Know
Experimentation
LaunchDarkly on LaunchDarkly: How we build better web experiences with experimentation

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Developer productivity
Check out our awesome new docs site
Developer productivity
Quickly Disable External API Calls in Your Sinatra Application Using LaunchDarkly Kill Switch Flags
Developer productivity
How to Implement Kill Switch Flags to a Spring Boot Application
Risk mitigation
Policies changing one day and being revoked the next? Adapt quickly using feature management
Experimentation
Experimentation starts with engineering: Why unifying feature delivery and experimentation is essential
AI
DeepSeek vs Qwen: local model showdown featuring LaunchDarkly AI Configs
AI
Compare AI Models in Python Flask Applications — Using LaunchDarkly AI configs
Experimentation
When does experimentation add value? A product manager’s guide
Risk mitigation
Guarded Releases: Why I’ll never go back to the old way of deploying software
Experimentation
LaunchDarkly + Snowflake: Introducing Warehouse Native Experimentation and Product Analytics
Risk mitigation
Software releases: navigating between innovation and user expectations
AI
Add DeepSeek-R1 to your Python app in 7 minutes with LaunchDarkly AI Configs
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Check out this study: LaunchDarkly Best in G2 2024

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