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Data Engineering & Analytics🔴Developer
T

Typedef

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

Starting atContact sales
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In Plain English

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

OverviewFeaturesPricingUse CasesFAQ

Overview

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.

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Key Features

Feature information is available on the official website.

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Pricing Plans

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    Best Use Cases

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    Refactoring legacy dbt projects safely at scale

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    Auditing downstream impact of a schema or column change

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    Debugging broken pipelines without paging the original author

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    Onboarding new analytics engineers to a sprawling warehouse

    Pros & Cons

    ✓ Pros

    • ✓Context-layer architecture solves a real failure mode of MCP-only agents
    • ✓Strong fit for large, messy dbt projects with significant tech debt
    • ✓Lineage-aware: agents understand the blast radius before they edit
    • ✓Covers debugging, refactoring, and onboarding in one product
    • ✓Vendor-neutral across Snowflake, BigQuery, and Databricks

    ✗ Cons

    • ✗Pricing is not published — demo-only sales motion
    • ✗Overkill for small dbt projects or greenfield warehouses
    • ✗Requires a mature analytics-engineering practice to deploy well
    • ✗Limited public documentation on advanced features

    Frequently Asked Questions

    How much does Typedef cost?+

    Typedef pricing starts at Contact sales. They offer a single pricing plan.
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    Quick Info

    Category

    Data Engineering & Analytics

    Website

    typedef.ai
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