4 workflows to adopt AI agents, beyond code generation

Automated RCA

Investigates iteratively and gets you to root cause

Triages and investigates alerts even before your on-call engineer gets started.

Starts investigating autonomously

As soon as an alert fires, Resolve AI begins investigation even before the on-call engineer starts.

Creates an investigation plan

Forms hypotheses based on your architecture, recent deployments, and system state to determine where to look first.

Pursues multiple hypotheses in parallel

Spawns specialized agents across logs, metrics, traces, infrastructure, and code running down each hypothesis simultaneously.

Continuously refines the plan as evidence emerges

Updates plan based on what agents find by ruling out paths that don't fit and doubling down on those that do.

Provides a working theory with the evidence behind it

Converges on the most likely root cause, ranked by confidence with the full evidence trail.

Find how Resolve AI gets you to root cause

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Engineering teams running Resolve AI in production

Engineering teams at Zscaler, DoorDash, MongoDB, and others run Resolve AI against every alert in their production systems.

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87% faster

root cause identification at DoorDash Ads

DoorDash Ads cut investigation time from 40 minutes to under a minute.

75% faster

incident investigations at Zscaler

Across 150,000+ alerts per month and 160+ global data centers.

30% fewer engineers

per incident at Zscaler

Resolve AI narrows the blast radius of every incident, reducing unnecessary escalations.

How Resolve AI gets you to root cause

Resolve AI connects to your production tools, investigates every alert the moment it fires, and surfaces a root cause grounded in your actual system architecture.

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