Custom superhuman SRE agents with full production context run the automation around every service.
Delegate the work across the lifecycle: monitors every deploy, answer questions, close alerts, write reports, and suggest what to fix next.
Describe the work once and ResolveAI spins up agents to do the job continuously, without you building or hosting anything.
Answers each ticket with what production shows. Links the alert, the deploy, or the issue behind it.
Watches each deploy on the signals and window you set. On drift it investigates, rolls back, or pages the owner.
Watches a service against its own baseline. Catches the anomaly early and mitigates it, or pages the owner.
Writes handoffs, postmortem drafts and weekly reports from live production data, with the evidence linked.
Deploy and service watches catch degradation before it pages anyone.
Primary on-call
Known issues and tried mitigations are in the investigation from minute one. MTTR drops.
Incident resolutions
Workflows hand the fix to coding agents, update the backlog, and close tickets.
Issue remediation
Knows your production, runs the work, stays in bounds.
On the critical path
Every deploy, every ticket, every Monday. Hivemind and the Production graph give each run the context a senior SRE would have.
Frontier production AI
SRE-1 makes each run fast and cheap enough to run on every deploy. Massively parallel reasoning verifies before it writes, rolls back, or replies.
Closes the loop
Scoped autonomy and Platform guardrails: each workflow runs with the access you grant, and every run leaves an audit trail.
Works within your guardrails.
Describe the work, the trigger, and the limits. ResolveAI sets it up and runs it. Nothing to build or host.
Each workflow runs with the access you grant, and nothing more. Read-only by default.
What it read, what it did, and who approved it, in one audit log you can open from the thread.
Two weeks to see ResolveAI hold your pager. Shadow first, then live per alert.