How Jarvis on OverWatch changed our ops rhythm

Running eight products in production is a different problem to running one. The maths compounds badly. Eight error feeds. Eight log streams. Eight dashboards. Eight slightly-different deployment pipelines. A steady drip of low-priority incidents that nobody has the cycles to triage — which then compound into the incidents you do have to deal with at 2am.

The team was spending more time watching the stack than building on it. Something had to take first-line watch.

Jarvis on OverWatch is what we built. It's an AI co-pilot that runs continuously against every product's telemetry. When it sees something wrong, it triages the severity, groups related incidents so a pattern doesn't show up as 40 tickets, files a single clean ticket with a drafted incident report, and pings the right person.

The magic isn't the AI. The magic is that we finally had a triage layer that never got tired, never forgot context, and had read the whole codebase.

The ops rhythm changed. Most weeks we now look at Jarvis's summary first thing Monday and see the incidents we didn't have to wake up for. Post-mortems arrive already drafted in the team's voice. The monthly executive briefing writes itself.

It's not perfect. Jarvis still misgroups some incidents. It still occasionally pages for something that wasn't actually user-impacting. We fix those edge cases as they come up. But the baseline has shifted: the team's attention goes to shipping, not watching.

We're not selling Jarvis externally. Yet. It's too tuned to our own stack right now. But every OnPoint Group client benefits from it indirectly — because the product we ship to you is monitored by the same AI layer we run our own revenue on.