Your self-hosted AI SRE
Root cause in minutes. Fix in a PR.
When something breaks, Operate finds out why by reading your logs, database, and code. Then it drafts the fix. Nothing ships without your approval.
Runs in your infrastructure · read-only · every step auditable
How Operate keeps your environment safe#production-alerts
14 members
DatadogAPP9:14 AM
P95 latency on checkout-api crossed 2.4s (threshold 800ms)
Priya · Support9:16 AM
@Operate customers reporting failed checkouts, what's going on?
OperateAPP9:27 AM
Root cause found92% confidence · verified
Migration 0142 dropped the index on orders.account_id. Every checkout now runs a full table scan.
logscheckout-api · 412 slow-query warnings on orders in 20 min
dbEXPLAIN: full table scan on orders.account_id (replica, read-only)
gitMigration 0142 dropped idx_orders_account_id · merged 14:02 UTC
Investigated in 11 minutes. No engineer interrupted
read-only · auditable
The problem
Every production issue pulls an engineer off real work.
When something breaks, someone has to stop building, dig through logs and data, and figure out why. It's slow, it can't be planned, and it usually lands on your best people.
Reported
A customer reports a bug
Support can't answer why. An engineer has to stop their work and dig in.
Silent
Something fails quietly
A background job dies and no alert fires. You find out when a customer leaves.
Slow
The app gets slower
Pages take a little longer every week. Users don't complain, they just stop using it.
30–40%
of engineering time goes to chasing production issues
3.2 hrs
to find the cause of a typical bug by hand
68%
of issues are the same problems coming back again
How it works
It watches, it answers, you approve.
Four AI agents read your logs, database, and code to work out what broke and why. A second AI model checks every answer before anyone sees it.
01 · Proactive
It finds problems on its own
Operate watches your alerts and errors around the clock. Nobody reported this one. It still got investigated and fixed.
#prod-alerts
DatadogAPP3:04 AM
Error rate on payment-webhooks crossed 4% (threshold 1%)
OperateAPP3:16 AM
Root cause foundverified
A retry loop in yesterday's deploy hammers the webhook endpoint when a payment fails. Evidence and fix attached.
Investigated at 3 AM. Your team read the answer at breakfast.
02 · On demand
Anyone on the team can ask
Product, support, or anyone else can ask in plain English from Slack, MS Teams, or whatever chat tool your team uses, and get a real answer. No engineering background needed, no waiting on an engineer.
#product
Maya · Product11:42 AM
@Operate users say search is broken since this morning. What changed?
OperateAPP11:51 AM
The search indexing job has been failing since 6:10 AM. This morning's deploy renamed a field the job depends on, so new items aren't searchable. About 8% of today's listings are affected.
A product manager got to root cause without pulling in an engineer.
Every fix stops at a draft PR. An engineer reviews the evidence and decides what ships. Nothing merges without human approval.
Security overviewSelf-hosted
Your infrastructure. Your data. Read-only.
Runs in your infrastructure. A Docker image alongside your app. No new cloud accounts, no SaaS endpoints.
Read-only, always. No write access to production. Every query is logged. The only write is opening a draft PR.
Data never leaves. Logs, records, and code stay inside your environment.
No black box. Every agent's reasoning is visible and auditable, end to end.
A growing context layer. 14 categories of context, from logs and code to feature flags and support tickets. Every connected source gives the agents more signal and a better root cause.
Your AI provider. Bring Claude (Anthropic), Codex (OpenAI/Azure), your enterprise model, or a self-hosted open-source LLM. Your keys, your terms.
↓ read-only adapters ↓
Operate
four-agent pipeline · your infrastructure
↓
Draft PR. Human approves, then it ships
60+ integrations across 14 kinds of context
The more of your stack Operate can see, the better its root causes. Don't see yours? Talk to us and we'll wire it up.
Source control
Logs
Databases
Chat
Error tracking
APM & tracing
CI/CD & deploys
Config & feature flags
Cloud & infrastructure
Queues & streams
Incident management
Issue tracking
Support
Status & docs
We love open source
Operate helps open-source projects too.
Point Operate at any public GitHub or GitLab repo and it reads the code, traces the root cause of an open issue, and drafts an explanation a maintainer can share. Free, no sign-up. Maintainers can use it on their own issues.
Already investigating 40 projects
Pricing
Transparent from day one.
No sales gate, no annual contract. Start self-serve, or have us run the whole pipeline for you.
Self-serve
$99/mo
+ usage, billed at flat rates by LLM mode:
- Operate Managed LLM — $4.50 / 1M input · $22.50 / 1M output
- Bring Your Own LLM (your API key or self-hosted) — $1.50 / 1M input · $7.50 / 1M output
- Full four-agent investigation pipeline
- Slack app, integrations, proactive monitoring
- Deploy via Docker in your own infrastructure
- Read-only access, fully auditable
Managed
Talk to Us
Operate deploys engineers who manage production systems for large enterprise customers, running on the Operate stack.
- We deploy and operate it inside your cloud
- We handle your issues and escalations end to end
- We review every finding and fix, and work with your team before anything is deployed
- We keep making the system smarter: new skills, better prompts, tuned to your architecture
- Weekly reporting, no long-term contract
Questions
The things engineers ask first.
On its own, an AI model can't see your logs, your database, or your code history. Operate is the layer that connects to all of them safely, plus the agents that turn what they find into a verified answer.
One agent proposes a root cause with specific evidence; a separate agent on a different model verifies it independently. Speculative conclusions are rejected before anyone sees them.
Nothing. All adapters are read-only. Operate never writes to your systems. Instead of opening PRs automatically, Operate generates a .patch file that your developers can review and apply manually.
Self-serve is a Docker image plus read-only credentials. Most teams are running within a day. Managed setups have us live inside your cloud within two weeks.
You can keep using the product as long as you have a positive credit balance. The subscription fee is only one way to maintain access; prepaid credit works too.
No. Credit is valid for the lifetime of your account and never expires.
From the blog
Field notes on RCA, observability, and shipping AI safely.
Stuck state: the failure mode behind both July 2 postmortems
Railway and CircleCI both published July 2, 2026 postmortems with the same hidden failure mode: state captured during instability that never corrected itself.
Reduce MTTR by attacking the 80 percent: diagnosis, not repair
About 80 percent of MTTR is spent finding the cause, not fixing it. A diagnosis-first playbook for reducing MTTR across code, database, infra, logs, and CI.
Beating On-Call Alert Fatigue: Triage by Evidence, Not by Threshold-Tuning
On-call alert fatigue is a triage problem, not a threshold problem. A practical guide to cutting page volume by investigating alerts to root cause across the whole stack.
Get your engineers back to building.
Let Operate handle the production fires. Deploy it yourself, or talk to us about running it for you.