Powering Quality KPIs with AI
More data. More dashboards to learn. More queries to master.
Same question: "What's broken and why?"
Faster dashboards. Easier queries.
But still no answer to: "Why is it broken?"
We asked ourselves:
The metrics that matter:
Not faster dashboards β faster root cause
Reliability reimagined with LLMs
No more generic answers. Context that understands your stack, your history, your patterns.
Ask questions like you talk. No query languages. No dashboard hunting. Just answers.
When systems grow beyond human comprehension, LLMs bridge the gap between complexity and clarity.
This is Olly
What services exist? What broke before?
Petabytes of logs β limited token window
Did it actually find the root cause?
Context of your environment
Not "did it sound smart?" β "did it find the bug?"
"We had checkout errors spike last night.
What changed and what's the likely cause?"
"Not just faster β smarter. Complex investigations become clear answers."
You ask, Olly investigates
Olly triages before you wake
Prevent before customers notice
Reactive firefighting β Proactive reliability
Questions?