Sidecar Data Information

Sidecar is the data operations and evals platform that gets data teams AI-ready, and keeps them there. Most data teams can’t say whether their platform is ready for AI. There’s no playbook and no way to measure it. Sidecar defines the dimensions that matter (data modeling, quality evaluations, AI surfaces, context and retrieval, and operating standards), then evaluates and scores each one. Evaluate, fix, evaluate again. A forward deployed engineer, included in every subscription, runs a full evaluation of your stack. They make the changes it needs and re-evaluate until it meets the standard. Agents run your data operations. Once you’re ready, Sidecar’s agents keep you there. They handle the ongoing work: data quality, metadata and context, tech debt, and warehouse cost. A job can start from a dbt failure, a Snowflake cost spike, a schema change, a Jira ticket, or a question in Slack. Every job ends in a concrete change your team reviews, such as a PR, a draft, or a report. A human stays in the loop before anything ships. Context your agents can trust. Context Garage is a governed, version-controlled context layer. It’s built from your warehouse, dbt, lineage, and real usage, and it powers Sidecar’s agents and any agent you bring. Sidecar works with Snowflake, BigQuery, Databricks, dbt, Fivetran, Looker, Hex, Omni, GitHub, and more. It’s SOC 2 Type II. Built by data people, for data people. Start a free trial at sidecardata.com.