Operate is a self-hosted AI SRE: an AI agent platform that detects, investigates, and resolves production issues. It runs a four-agent pipeline (Context, Root Cause, Verification, and Resolution) that connects to your logs, database, and codebase, then produces an evidence-backed root cause and a draft pull request for human review.

An AI SRE is an AI system that does the work of a site reliability engineer: watching production for errors and regressions, investigating alerts, finding root causes, and proposing fixes. Operate is a self-hosted AI SRE, so it runs inside your own infrastructure with read-only access and a mandatory human approval gate.

How does Operate find the root cause of a production issue?

When triggered from chat (Slack, MS Teams, and other tools) or by an automated alert, Operate pulls traces from log providers like Datadog, CloudWatch, GCP Cloud Logging, and SolarWinds, queries your MongoDB, PostgreSQL, or MySQL database in read-only mode, and reads your codebase via git including blame and diff. A Context Agent gathers signals, a Root Cause Agent proposes a cause with a confidence score, a Verification Agent independently checks the reasoning with a different model, and a Resolution Agent drafts a fix as a pull request.

Does Operate ship code automatically without a human?

No. Operate stops at a draft pull request. A human engineer must review and merge; nothing ships without approval. Every agent step is auditable so reviewers can see the evidence and reasoning behind each finding.

How is Operate deployed?

Operate is deployed as a Docker image into your existing infrastructure with no new cloud accounts. It runs on port 8080 under the /operate path, requires MongoDB and Redis, and uses an App ID from operate.bettrsw.com. It connects via read-only adapters to logs, databases, and observability stacks, and clones your repo at startup via an init container so agents have full git history.

Which integrations does Operate support?

Operate's context layer spans 60+ integrations across 14 categories: source control (GitHub, GitLab), logs (Datadog, CloudWatch, GCP Cloud Logging, SolarWinds), databases (MongoDB, PostgreSQL, MySQL, read-only), error tracking (Sentry, Rollbar), APM (New Relic, Grafana, OpenTelemetry), CI/CD (GitHub Actions, Jenkins, Vercel), feature flags (LaunchDarkly, Statsig), cloud infrastructure (AWS, GCP, Azure, Kubernetes), queues (Kafka, SQS, RabbitMQ), incident management (PagerDuty, incident.io), issue tracking (Jira, Linear, Asana), support (Zendesk, Intercom), status pages, and docs (Confluence, Notion). Triggers: Slack, MS Teams, and other chat tools for on-demand RCA, plus the observability stack for proactive monitoring. AI providers: Anthropic Claude, OpenAI/Azure Codex, enterprise models, or self-hosted open-source LLMs.

How does Operate avoid hallucinated root causes?

Operate uses a two-model verification step. The Root Cause Agent proposes a cause with specific evidence; the Verification Agent, running on a different model to avoid correlated errors, independently evaluates the reasoning. Speculative or unsupported conclusions are rejected before reaching the team.

Why not just point an LLM at our logs ourselves?

An LLM has no inherent knowledge of your logs, schemas, services, or known-bad patterns. Operate provides the connectors, permissions, query layer, repo context, multi-agent verification, and operational runtime that turn a generic model into a reliable production-investigation system.

Engineering teams that lose 30–40% of capacity to unplanned investigation: support escalations, error alerts, performance regressions. With Operate, support and product teams can trigger an RCA from Slack, MS Teams, or whatever chat tool they use, and only loop in engineers when a decision needs to be made.

← All repos

github

AppFlowy-IO/AppFlowy

Pick an open issue and Operate will investigate its root cause.

917 open issues

#8867 [Bug] Unexpected Data Loss - Dates in Grid have suddenly all automatically changed to a random date in 1970.
bug
grid
database
#8865 [Bug] msg: Internal failure: code:Record not found, message:Record deleted:Database/6db3f828-765c-414c-b108-84e28d015086 is not active in db
bug
#8863 Login is broken.
bug
#8862 [Bug] [import] [Notion] Notion import error
#8861 [FR] Subpage Directory
#8860 [Bug] Link hover popup blocks scrolling and intercepts Backspace, Delete and arrow keys
#8859 [Bug] Cards with End Date toggled can not be dragged and dropped across Calendar view
calendar
#8857 [Bug] Mobile: ai can create, edit , add and access to any page
AI
database
#8856 [Bug] Time selector is buggy!
#8854 [Bug] Linux installation issues
#8853 [Bug] unable to drag a row to a position that's out of the current view
bug
table
#8852 [Bug] mention a simple table's copy link to block not following the mention style
bug
table
Q3 26
#8851 [FR] the ability to copy a simple table
table
copy-paste
Q3 26
#8849 [Bug] docs: Broken Inlang translation link in README (404 Error)
#8848 [Bug] Cursor lose focus when moving up from the first line (seen on a page in a dataset)
bug
platform-linux
#8845 [Bug] I can’t open the document, it’s giving an error message
#8844 [Bug] On mobile (android) I can't open a database row as a page
#8842 [Bug] PopOS Cosmic 24.5 upgrade problems
#8840 [FR] i18n Russian translations
i18n
#8839 [FR] Question / Feature Request: SECURITY - Sessions remain active across devices after password change
Q3 26
#8834 [BUG] columns in kanban board losing their coloring
bug
kanban board
#8832 [FR] Notion-like blank toggles
improvements
editor
#8831 [BUG] Android slowness after clicking on text
#8829 [Bug] Cards and Groups disappear.
bug
kanban board
#8828 [Bug] Right-to-Left alignment set as auto doesn't work inside tables
improvements
table
#8826 Improving Reminders
#8824 Grid horizontal scroll misalignment - header doesn't stay fixed after switching between windowed and fullscreen mode
#8823 [FR] Support for recurring tasks and date range tasks
#8822 [FR] Notion-like arrow key navigation
bug
editor
#8821 [FR] Notion-like highlighting ability