Launching Resolve AI Labs backed by new $40M Series A Extension
Proactively run tasks like deployment monitoring, operational reports, and resource optimization on a schedule or on trigger.
Run your workflows on a cadence, or fire agents on event triggers like deploys, alerts, and other production events.
Tasks like deployment monitoring, operational reports, resource optimization, and more with a template library to start from.
Background agents pre-investigate every item so you open Resolve to verified findings and recommended next steps.
Use chat for live debugging, multi-turn investigations, or to trigger background agents on demand.
Removing the toil of investigations, war rooms, and on-call.
We pull fewer engineers into war rooms, on-call is materially better, and that translates directly to advertiser trust and revenue protection.
Shahrooz Ansari
Sr. Director of Engineering, DoorDash
I don't need more numbers or more data. What I need is a root cause.
Chris Umbel
AIOps Lead & SRE, Zscaler
Resolve AI proved it could deliver real results in a constrained environment. It identified dependencies, surfaced accurate root causes 73% faster than our teams, all while integrating cleanly into our existing stack.
Angelo Marletta
Staff Software Engineer, Coinbase
Resolve AI makes our junior on-call engineers as effective as our seniors, flattening the experience curve. We've seen a 2x productivity lift while eliminating the runbook gap.
A.D.
Sr. Director of Engineering, Financial Services Company
We pull fewer engineers into war rooms, on-call is materially better, and that translates directly to advertiser trust and revenue protection.
Shahrooz Ansari
Sr. Director of Engineering, DoorDash
I don't need more numbers or more data. What I need is a root cause.
Chris Umbel
AIOps Lead & SRE, Zscaler
Resolve AI proved it could deliver real results in a constrained environment. It identified dependencies, surfaced accurate root causes 73% faster than our teams, all while integrating cleanly into our existing stack.
Angelo Marletta
Staff Software Engineer, Coinbase
Resolve AI makes our junior on-call engineers as effective as our seniors, flattening the experience curve. We've seen a 2x productivity lift while eliminating the runbook gap.
A.D.
Sr. Director of Engineering, Financial Services Company
Proactive, time-triggered checks on a cadence.
Agents watch rollouts and investigate before alerts fire.
Configure at org, team, and personal levels.
Start from proven workflow patterns and customize.
Automated knowledge capture after every interaction.
Watches #engineering for deploys; runs post-deploy health checks.
On deploy event
Posts daily deploy + incident digest at 7 AM PT.
Daily at 7:00 AM
Monitors orders-db-cluster for query regressions and lock contention.
On alert event
Weekly resource-utilization report across clusters and services.
Weekly · Fridays
Triggered by a deploy notification in #engineering (compare URL, smoke test link, "deploy kicked off"). Post all updates in the deploy thread.
| Environment | Type | Log channel | Cluster |
|---|---|---|---|
dev0 | Pre-prod (staging) | #engineering-log-dev | dev0-cluster |
app0 | Production | #engineering-log-prod | app0-cluster |
rocket | Production (dogfood) | #engineering-log-prod | app0-cluster |
Environment progression: dev0 → app0 → rocket. Each gates the next.
{github_run_id}.{attempt}-{7_char_sha} (e.g. 24893095514.1-dac7506). The github_run_id is the dev0 build run, not the prod deploy run.Before running the health check, verify the prod deploy pipeline completed successfully for this deploy tag (Deploy to Cells workflow for app0, Deploy to Rocket from Cells for rocket).
Good morning. Overnight, agents reviewed 47 items across 6 channels.
4 need your attention · 2 scheduled for today · 41 resolved cleanly
Finding: Deploy 8ab7b0a hasn't started on app0-cluster — previous deploy still in progress. Health check will run once the rollout begins.
Finding: Scheduled 8:00 AM run did not fire — agent was unresponsive between 04:35–16:29 UTC. Will resume on the next scheduled run tomorrow.
Finding: Likely candidate: new code path in order-fulfillment.ts hits a slow query at p99 only under load. Re-checking after next traffic window.
Finding: Caught at deploy time and rolled back cleanly. No customer impact recorded. No further action needed.
What's going on with checkout-router p99 today? Is it the deploy at 10:14 PT?
Yes — drift starts ~2h after the deploy. p99 was steady at ~142ms through 12:00 PT, then climbed to ~387ms as traffic ramped.
Likely candidate: new code path in order-fulfillment.ts hits a slow query at p99 only under load. Error rate and throughput look normal — this is latency-only.
Set up an agent to watch checkout-router latency after every deploy going forward. Alert me if drift >25% within 2h.
Done. I'll watch every deploy that touches checkout-router and alert you if p99 drifts more than 25% within 2 hours.
Background agent created