Executive summary
From alert to validated fix
FixBugs is the AI debugging platform from Modulo AI. It uses huge-context reasoning to turn production signals and bug reports into debugging insights, root-cause hypotheses, validated fixes, and reviewable pull requests.
Huge context reasoning
FixBugs assembles the bug report, repository context, linked issues, recent changes, logs, traces, metrics, screenshots, and videos before choosing a path.
Validation-first fixes
The workflow aims to reproduce the issue, propose the change, and attach validation output before a human decides whether to merge.
Collaborative
Triage sessions, hypotheses, decisions, diffs, and validation notes stay shareable so another engineer can pick up the investigation without restarting from scratch.
Core insight
FixBugs is a multi-agent workflow that triages alerts, detects bugs and resolves them. It gathers the full context, turns it into ranked insights, validates the fix path, and keeps engineers in control.
Why the category exists
Coding agents are useful when the developer already knows what they want to build. Debugging is different. The relevant context usually lives across issue threads, alerts, traces, logs, screenshots, recent deploys, and source history.
Continuous Bugfixing is the missing layer between observability and resolution. Monitoring tools tell teams something broke. FixBugs works through the evidence chain and prepares the fix path.
What a workflow produces
- A normalized bug input from an alert, issue, ticket, or raw report.
- Analysis-backed ranked hypotheses with cited context.
- A fix plan that shows affected files and intended changes.
- A reviewable diff and validation output.
- A PR-ready artifact when the analysis and validation are strong enough.
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