Datafold

Datafold is an automated data engineering platform designed for enterprise data teams, analytics engineers, and data architects. It automates data platform migrations, pipeline refactoring, and quality monitoring using specialized AI agents combined with automated data validation.

The platform features a Data Knowledge Graph that unifies column-level lineage, business logic, usage patterns, and repository source code. By exposing this context layer and testing tools via Model Context Protocol (MCP), Datafold provides external coding agents with structured context to generate reliable pipeline code and perform regression testing.

Datafold can be deployed inside a single-tenant Virtual Private Cloud on AWS, GCP, or Azure, enabling compliant LLM inference while keeping source code and datasets within the enterprise security perimeter.

Key features

• Data Migration Agent: Automates code translation and performs continuous data parity checks to migrate legacy data stacks to modern warehouses.
• Data Knowledge Graph: Automatically indexes repository code, column-level lineage, and domain logic, serving context to AI tools via MCP.
• Data Diff: Compares datasets row-by-row and column-by-column in CI/CD workflows to catch value-level data regressions before deployment.
• AI Code Reviews: Generates automated summaries of pull requests, analyzes root causes for data shifts, and provides context-aware chat for debugging.
• Data Monitoring: Tracks data freshness, volume, and distribution anomalies across data warehouses and exposes status programmatically via MCP.