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The Context Layer

Cost & Performance Tune-ups

Automated Data Catalog

Turn tickets into shipped data work with the Sidecar Engineer

Assign a ticket. Sidecar plans it, does the work, and ships a PR or document for your review

Understands the work before touching anything

Sidecar reads the ticket, gathers context from your warehouse, dbt project, and lineage, and outlines a clear plan directly in the thread so your team can review or steer.

Executes real data work in your stack

Builds and updates dbt models, investigates data quality issues, reconciles metrics, and improves performance, directly where the work lives.

Ships with full visibility

Posts updates in JIRA, Linear, or Slack, explains decisions along the way, and delivers a clean pull request ready to review and merge.

Built for the data team.

Purposefully transformed context from your data platform, your data operations tooling, and your business context

Industry-leading context.

Outperforms existing context solutions on industry benchmarks

Context where you work.

Plugs into your favorite AI tools like Cursor and Claude Code

Drive better AI outcomes using context built specifically for data people

Sidecar’s context layer specifically combats context bloat, MCP tool fatigue, and unnecessary token consumption

Sidecar scans backend repositories for relevant changes

Any change that would affect the data team gets flagged as a Github comment

Detect breaking changes in CI/CD.

When upstream changes occur, Sidecar detects them during deployment and notifies the data team before pipelines break.

Automatic remediation.

Sidecar opens pull requests with the required modeling updates so downstream transformations stay in sync with source changes.

Prevent breaking changes before they hit production with the Sidecar Contract Agent

Sidecar ensures consumers responds appropriately when producers make data and schema changes at source

Stop running “tech debt” sprints

Sidecar continuously analyzes your warehouse usage and data pipelines to surface the fixes that actually reduce cost and improve performance

Find wasted spend.

Identify expensive queries, deprecation opportunities, inefficient models, and redundant compute usage across your warehouse before they become a budget problem

Actionable fixes, not dashboards.

Sidecar doesn’t just highlight issues, it takes action on your behalf

Continuous optimization.

Tune-ups run automatically as your platform evolves, preventing performance regressions and cost creep

A catalog that builds itself

Sidecar automatically generates and maintains documentation using signals from your warehouse, transformation tools, and operational metadata

Documentation without the work.

Automatically generate table descriptions, column definitions, and lineage so your catalog stays complete without manual effort

Context beyond the warehouse.

Enrich metadata with signals from tools like dbt, orchestration systems, and other operational tooling

Always up to date.

As pipelines evolve and schemas change, Sidecar keeps documentation synchronized with the actual state of your platform

Understand your data platform at every level, visually

Hubble gives you a unified view of pipelines, lineage, and dependencies across your entire data stack

End-to-end lineage.

Trace data from source systems through ingestion, transformation, and analytics to understand exactly where datasets originate

Explore complex DAGs easily.

Navigate massive data graphs with filters, highlights, and exploration tools built for real production data platforms

Ensure compliance.

Identify what parts of your platform are compliant and what changes need to be made

Understand your data platform at every level, visually

Hubble gives you a unified view of pipelines, lineage, and dependencies across your entire data stack

End-to-end lineage.

Trace data from source systems through ingestion, transformation, and analytics to understand exactly where datasets originate

Explore complex DAGs easily.

Navigate massive data graphs with filters, highlights, and exploration tools built for real production data platforms

Ensure compliance.

Identify what parts of your platform are compliant and what changes need to be made

Understand your data platform at every level, visually

Hubble gives you a unified view of pipelines, lineage, and dependencies across your entire data stack

End-to-end lineage.

Trace data from source systems through ingestion, transformation, and analytics to understand exactly where datasets originate

Explore complex DAGs easily.

Navigate massive data graphs with filters, highlights, and exploration tools built for real production data platforms

Ensure compliance.

Identify what parts of your platform are compliant and what changes need to be made

Pipeline reliability monitoring.

Track freshness, failures, and anomalies across ingestion and transformation pipelines

Proactive issue detection.

Detect schema changes, unexpected data shifts, and missing updates automatically

Focused alerts, not noise.

Surface the issues that actually impact downstream consumers instead of flooding teams with low-signal alerts

Catch data issues before your stakeholders do

Sidecar monitors pipeline health, freshness, and anomalies so problems are identified before they impact the business

Pipeline reliability monitoring.

Track freshness, failures, and anomalies across ingestion and transformation pipelines

Proactive issue detection.

Detect schema changes, unexpected data shifts, and missing updates automatically

Focused alerts, not noise.

Surface the issues that actually impact downstream consumers instead of flooding teams with low-signal alerts

Catch data issues before your stakeholders do

Sidecar monitors pipeline health, freshness, and anomalies so problems are identified before they impact the business

Governance that actually works for data teams

Sidecar automates governance workflows so teams can enforce standards without slowing development

Automatic classification.

Detect sensitive data like PII and apply governance tags across tables and columns

Policy enforcement.

Define governance rules once and apply them consistently across your data platform

Audit-ready visibility.

Maintain clear ownership, lineage, and usage visibility for regulatory and internal governance needs

Governance that actually works for data teams

Sidecar automates governance workflows so teams can enforce standards without slowing development

Automatic classification.

Detect sensitive data like PII and apply governance tags across tables and columns

Policy enforcement.

Define governance rules once and apply them consistently across your data platform

Audit-ready visibility.

Maintain clear ownership, lineage, and usage visibility for regulatory and internal governance needs

Governance that actually works for data teams

Sidecar automates governance workflows so teams can enforce standards without slowing development

Automatic classification.

Detect sensitive data like PII and apply governance tags across tables and columns

Policy enforcement.

Define governance rules once and apply them consistently across your data platform

Audit-ready visibility.

Maintain clear ownership, lineage, and usage visibility for regulatory and internal governance needs

Try it yourself

Let Sidecar make your team feel 10x bigger

Automate your operations and give agents context

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