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%.
Manual reviews couldn't keep pace. Claude now uses IDE tools to validate logic, cutting first reviews from hours to minutes.
A flood of AI code overwhelmed reviewers. Now, agents trace logic to catch bugs static tools miss, securing 1M pull requests quarterly.
AI coding tools outpaced manual review. Reasoning models now audit complex logic, cutting pull request cycles by up to 50%.
Manual reviews couldn't keep pace. Claude now uses IDE tools to validate logic, cutting first reviews from hours to minutes.
Scattered spreadsheets couldn't catch AI hallucinations. Now, automated LLM judges evaluate every prompt change to block regressions.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Hundreds of pages per board book slowed director prep. Now, isolated AI securely condenses sensitive materials into actionable briefs.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.
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%.
Manual reviews couldn't keep pace. Claude now uses IDE tools to validate logic, cutting first reviews from hours to minutes.
A flood of AI code overwhelmed reviewers. Now, agents trace logic to catch bugs static tools miss, securing 1M pull requests quarterly.
AI coding tools outpaced manual review. Reasoning models now audit complex logic, cutting pull request cycles by up to 50%.
Manual reviews couldn't keep pace. Claude now uses IDE tools to validate logic, cutting first reviews from hours to minutes.
Scattered spreadsheets couldn't catch AI hallucinations. Now, automated LLM judges evaluate every prompt change to block regressions.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Hundreds of pages per board book slowed director prep. Now, isolated AI securely condenses sensitive materials into actionable briefs.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.