DataFuse Engineering & DevOps

Make Incident Response and Code Quality Automated

Connect your AI agent to developer tools. Sync Sentry crashes with GitHub source lines, write automated PR code-reviews, and page DevOps engineers immediately on PagerDuty.

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Works across your stack

SentryGitHubLinearDatadogPagerDutySlack

Illustrative workflows

See how the tools work together.

These examples show the intended sequence and are not live customer executions.

Example request

Check Sentry for any new unresolved production issues, find the failing code in GitHub, and log a ticket in Linear.

01
Initializing DevOps Issue Triaging Agent
02
Fetching unresolved production errors from Sentrysentry.list_unresolved_issues({ project: "datafuse-frontend", limit: 3 })
03
Spinning up isolated standard workbench sandboxsandbox_size: "standard" (1 vCPU / 1 GB RAM)
04
Downloading repository and running test suite in workbench sandboxDATAFUSE_REMOTE_BASH_TOOL.execute({ command: "git clone https://github.com/omnithium/datafuse.git && cd datafuse && npm test" })
05
Applying session?.user?.token optional chaining fix to workspaceDATAFUSE_REMOTE_WORKBENCH.patch_file({

One integration layer

Powering High-Velocity Dev Teams

Integrate error reporting, issue trackers, version control, and on-call paging into unified automated pipelines. Decouple auth from code execution safely.

Broad coverage

Start with the catalog and add custom APIs without creating a separate agent architecture.

Connected-user auth

Keep connection setup and tool execution in a dedicated server-side flow.

Clear execution history

Inspect what was called and whether it completed without reading raw application logs.

Build the workflow

Connect the first tool and keep moving.

Start free, then add integrations as the agent takes on more work.

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