Typedef Review 2026

Data engineering agents that analyse impact, refactor models, and debug pipelines with a continuously updated map of your data stack.

Typedef is a data engineering platform that uses a fleet of AI agents to do the unglamorous, time-consuming parts of data work: impact analysis across dbt models, schema refactors, lineage-aware code changes, and pipeline debugging. Its differentiator is a 'data context layer' that continuously maps your data stack — warehouses, BI tools, transformation projects, orchestrators — so agents always plan changes against the current state rather than a stale screenshot. Typedef has been vocal in pointing out that MCP alone only gives agents access; without a context layer, agents do not actually understand what they are changing. Common use cases include refactoring deprecated columns across hundreds of dbt models, debugging broken Airflow/Dagster pipelines, evaluating the downstream impact of a proposed schema change before merging, and onboarding new engineers via interactive explanations of unfamiliar models. Typedef is sold to platform and analytics-engineering teams; the company is currently demo-led with pricing disclosed under NDA. Best for mid-to-large data teams whose dbt project has grown faster than their ability to safely change it.