When a critical service fails, there can be thousands of log lines and a single root cause. Engineers search logs and old tickets by hand while the incident clock runs. Incident Assistant investigates like an experienced engineer and recommends the fix, with the evidence to back it.
Finding the root cause means sifting through huge volumes of logs under time pressure.
The answer is often in a past ticket that nobody on the current shift remembers.
AI tools that answer with confidence but no evidence are hard to trust in a regulated environment.
Incident Assistant investigates an incident and recommends a fix, citing every source it used. It advises, and your team makes the call.
It looks for error patterns in the logs and checks them against tickets your team has already solved.
It returns a likely root cause, a recommended fix and a confidence level, with every claim tied to the log lines and tickets behind it.
Every search runs inside boundaries you define, so each recommendation can be checked before anyone acts on it.
You see what it searched, what it found and why it reached its answer.
Every accelerator on this page started as a problem we needed to solve. If you’re facing a similar one, we’ll show you the working version and help you judge whether it fits.
A live 30-minute walkthrough of any accelerator on synthetic data, with the engineers who built it.
A working session to match your use case to what the lab has proven, and to be clear about what it hasn’t.
A time-boxed pilot in your environment, with the evidence trail your risk team will ask for.
