Pinpoint root causes with AI
and live runtime intelligence
The Lightrun AI Debugger uses live runtime context to turn noisy incident reports into clear, testable hypotheses you can validate in live environments without redeploying.
Turn tickets into action items, in moments
Lightrun’s AI transforms incident reports into concise, testable hypotheses for immediate validation using live runtime context.
Accelerated
incident triage
AI analyzes incident descriptions, logs, and alerts to build a focused plan of attack and next steps.
Clear, testable
hypotheses
AI uses authorized runtime context to translate vague symptoms into specific, testable checks for likely root causes.
Less noise,
more signal
Skip noisy dashboards and long ticket threads. Jump straight to a shortlist of realistic explanations you can quickly prove or disprove.
AI accuracy powered by runtime intelligence
Under the hood, Lightrun combines code-aware models with live runtime context so its suggestions map directly to real behavior in your systems.
Partner with AI to guide each investigation
Lightrun’s AI turns incident details into a guided sequence of steps, prioritizing the most likely causes and the most effective ways to validate them.
AI-driven
incident intake
Paste an incident description, log snippet, or alert into the AI Debugger and receive a structured investigation plan with suggested next steps.
Smart hypothesis
generation
The system proposes likely conditions, code locations, and data points to inspect so you can focus on validation rather than guesswork.
Guided
investigation flow
Instead of manually scanning logs and traces, follow an AI-guided sequence of checks that keeps you focused on the most likely causes.