Product
Two products, one consolidated data ops platform
Context Garage keeps a live model of your stack. Agent Console puts it to work. Together they replace the pile of point tools you use for cost, cataloging, and observability.
Context Garage
One versioned context layer for your whole stack
Sidecar synthesizes schemas, lineage, query logs, dbt projects, and the Slack and ticket threads around them into one governed source of truth that stays current automatically and is servable to any tool or agent you already use.
- Warehouse, dbt, BI, and lineage modeled together
- Version-controlled, so you can see what changed and why
- Serve it to Sidecar agents or bring your own
Agent Console
The fastest way to run agents for data
Kick work off from Jira, Linear, or Slack and watch every step against your real stack. Sidecar plans in context, does the work, and returns a reviewable pull request, with a human in the loop every time.
- Ships with 50+ job templates, and a studio for building your own
- Real-time visibility into every decision the agent makes
- Outcomes land as PRs, drafts, or reports where you work
Consolidated data ops
Retire the point tools for the unglamorous work
Cost and performance automation, cataloging, and observability run on the same context layer, so they agree with each other and stay current on their own.
Cost & performance tune-ups
Continuously profile warehouse spend, find the queries and models burning credits, and ship the fixes as reviewable pull requests.
Automated catalog
Descriptions, ownership, and column-level meaning derived from how your data is actually used, so nobody has to work through a documentation backlog.
Hubble explorer
Trace any metric from dashboard to source table, see what changed, and understand blast radius before you touch anything.
Data observability
Freshness, volume, and schema monitoring with tests Sidecar writes for you, plus root-cause context attached to every alert.
Data governance
Track PII, enforce naming and testing standards, and keep access policies in step with how the platform evolves.
Technical debt cleanup
Deprecate unused tables, untangle duplicate models, and backfill missing tests continuously, so the backlog shrinks without a dedicated sprint.
Technical debt sprints, without the sprint
Deprecate unused tables, backfill test coverage, and document the models people actually query, continuously, rather than in a quarter you never get to.