Reviewers struggled to predict how code ripples through the system. AI now flags cross-service risks that cause outages.
One of the world's most widely-used observability platforms helps companies monitor and troubleshoot complex distributed systems, making reliability critical before code reaches production.
Effective code review relied on senior engineers with deep historical context, as traditional static analysis tools were too shallow or noisy to...
“Time savings are real and important. But preventing incidents is far more compelling at our scale.”
Observability and security platform for cloud-scale monitoring and analytics.
AI research and deployment company developing generative models and tools.
Related implementations across industries and use cases
AI coding tools outpaced manual review. Reasoning models now audit complex logic, cutting pull request cycles by up to 50%.
Code reviews delayed releases while early AI hallucinated. Claude now validates logic to catch subtle bugs with one-click fixes.
Manual reviews couldn't keep pace. Claude now uses IDE tools to validate logic, cutting first reviews from hours to minutes.
Engineers manually correlated alerts across systems. AI agents now diagnose issues and suggest fixes, cutting recovery time by 35%.
Minor edits required days of crew coordination. Now, staff use avatars to modify dialogue and translate languages instantly.
Lab supply orders were handwritten in notebooks. Digital ordering now takes seconds, saving 30,000 hours for research annually.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.