01ON-CALL
Primary on-call
Holds the pager. Triages and mitigates alerts, escalating only when you are needed.
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Shaping the future of software engineering
By world-class engineering teams.
Owns on-call and improves production, within your guardrails
ResolveAI holds the pager, closes most pages on its own, escalates the rest with the root cause ready, and fixes what keeps paging.
80%
of pages closed on its own
10x
faster MTTR for alerts, incidents, and tickets
Closes pages and cuts MTTR, with high accuracy at low cost.
Our domain models and agent architectures, with the best frontier models, orchestrated for the one correct answer at the lowest cost.
| Metric |  Model | Claude Code |
|---|
SignalsAlerts · Incidents · Tickets · Tasks
01
Knows your live system
“ResolveAI has moved us from hours to minutes for investigations.” – Shahrooz Ansari, Senior Director of Engineering
Read the full story“Investigations went from hours to minutes...”
Running in production at global scale in the most regulated and security conscious environments.
64%
fewer incidents as root problems get fixed
03Issues
Fixes recurring issues by finding root problems and giving the production context to coding agents.
04Operational tasks
Build custom SRE agents for any automation you need, fully managed for you.
| LatencyMedian investigation time on hard incidents | 12 min | [X] min | 21 min |
|---|---|---|---|
| Average accuracyInvestigations with a usable root cause | 72% | [X]% |
Source: ResolveAI evals on human-annotated production incidents, [month year]. [X] = number pending sign-off.
Read the eval methodology02
SRE-1 · our domain model
03a
Noise, known issues, benign patterns
03b
New or urgent, with the proposed fix for the quickest resolution
04
Within your limits, until it clears
05
Finds the root problems creating alerts, incidents, and tickets
Resolvedfewer signals next time
| Accuracy on hard incidentsPass rate on the hardest production cases | 48% | [X]% | [X]% |
|---|
| Tokens usedPer investigation | [X]k | [X]k | [X]k |
|---|
