About
The AI coworker your engineers won't hate.
The Discovery
One of our interns was stuck on a production issue. Legacy Java app, no docs, nobody around who remembered how it was deployed. He got frustrated and pointed an LLM agent at the server.
It found the root cause in twenty minutes. It also restarted two services and took the app down for an hour. The diagnosis was right. The damage was also real.
That incident got us thinking. What if we had tooling around this? Read-only pipelines, parallel system reads, every destructive command blocked before execution. Keep the investigation. Remove the risk.
What We Built
It’s been great at diagnosing issues. But what surprised us was everything else. The structured reports, the log collection, the way it compiles evidence and cites what it finds.
That part used to take hours. Pulling logs, cross-referencing timestamps, writing it all up so someone else could understand what happened. Fawdy does that in minutes and the output is clean enough to hand to a VP or drop straight into a postmortem.
We built Fawdy for ourselves. It’s the tool we kept wishing existed every time we had to investigate a server and then explain what happened to everyone else.
From alert to report
20 min
Fawdy diagnoses the incident, compiles the evidence, and hands you a structured report. Ready to share, not raw terminal output.
Evidence compiled
All of it
Logs, configs, processes, metrics. Fawdy pulls it all together and cites every finding so nobody has to re-gather it.
Setup required
Zero
Fawdy plugs into the access controls you already use. No agents to install, no daemons to manage, no new ports to open.
Team
Built by people who’ve lived the on-call life
We’ve spent years in managed services and system administration, and we’ve built companies from scratch. Fawdy comes from that experience.
Some of the companies our team has worked at:
Fawdy is the tool we needed and didn’t have.
FAQ
Everything you need to know
Common questions about how Fawdy works.