These docs cover the Datafold application only. They do not cover Datafold’s AI agent platform, which our team uses to deliver migrations and other data engineering projects. The platform is changing quickly, so we share its capabilities directly rather than in public docs. To learn what it can do for your project, book a demo.
You are reading the docs for Datafold Classic (
app.datafold.com, eu.datafold.com, or a Classic Dedicated Cloud deployment). If you sign in at us.datafold.com, eub.datafold.com, or a deployment set up for a migration project, switch to Current in the version menu. Not sure? See Which version am I on?Key features
Data Platform Migrations
The Data Migration Agent delivers guaranteed-outcome migrations with fixed price, timeline, and data parity — over 6x faster than traditional approaches.
Data Explorer & Lineage
Explore lineage, business logic, and usage metadata across your data ecosystem.
Data Quality & CI/CD
Value-level data diffs, monitors, and reconciliation power tools — exposed via MCP so your coding agents can validate their own work.
MCP Integration
Connect your AI coding agent to Datafold and interact with your data through natural language — diffs, lineage, monitors, and more.
Use cases
Data Platform Migrations
Modernize your data platform in weeks, not years, with AI-powered migration automation and cross-database validation.
AI-Assisted Data Development
Supercharge your coding agents with data quality tools via MCP.
CI/CD Testing & Monitoring
Automatically test, data-diff, and validate every pull request before it reaches production.
Getting started
There are a few ways to get started with your first data diff:1
Create a data diff
Once you’ve integrated a data connection and code repository, you can run a new in-database or cross-database data diff or explore your data lineage.
2
Create automated monitors
Create monitors to send alerts when data diffs fall outside predefined ranges.
Learn more
- Connect your AI agent to Datafold via MCP and start using data diffs, lineage, and monitors from your development environment
- Read our Data Quality Guide for a practical roadmap to building a robust data quality system
- Book a demo to see how Datafold can automate your data engineering workflows
