Datafold

Datafold is the data engineering automation platform. AI-powered migrations delivered in weeks with guaranteed outcomes, plus data quality tools for CI/CD testing, monitoring, and AI agent integrations.

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Founded: 2020
Headquarters: New York City, NY, USA; Remote
Company size: Not disclosed
Products tracked: 6

Products by Datafold

6 products

Data Platform MigrationsThe Data Migration Agent delivers guaranteed-outcome migrations with fixed price, timeline, and data parity — up to 6x faster and cheaper than alternatives.0.00 reviewsData Integration & ETL

AI AgentsSpecialized AI agents for migrations, optimization, and code reviews.0.00 reviewsData Integration & ETL

Data Knowledge GraphThe context layer that makes your AI agents effective for data engineering by serving lineage, business logic, usage, and organizational knowledge via MCP.0.00 reviewsData Quality & Observability

Data Quality PlatformData Diff in CI/CD, cross-system reconciliation, proactive anomaly detection — all exposed via MCP so coding agents can test, debug, and validate programmatically.0.00 reviewsData Quality & Observability

Data DiffCompare datasets within or across databases with value-level precision at any scale.0.00 reviewsData Quality & Observability

Anomaly DetectionML-driven monitoring across all dimensions of data quality.0.00 reviewsData Quality & Observability

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Across industriesDetect Data Anomaliesvia Anomaly Detection#3Data, Analytics & Decisions Across industriesIntegrate Datavia Data Platform Migrations#10Data, Analytics & Decisions

Customer voice

Customer testimonials

Quotes published on Datafold's official website.

Having Datafold in a situation where you need 1 to 1 migration is critical The process for applying Datafold’s Data Diff capability on the data models was heavily based on ownership, collaboration, and accountability. Faire followed a series of steps to provide consistent data deliverables at a high level of accuracy.

Customer testimonialOn Data DiffOriginal

Seeing statistics and visualizations on how new model data compares to existing model data makes it easy to verify our migration SLAs with stakeholders. We saved 900+ hours in our migration to Snowflake.

Customer testimonialOriginal

The Datafold process — translating with the right LLM, validating the results, and letting humans review what falls out — is how I'd recommend every migration be done. It's faster, more accurate, and eliminates many sources of human error, especially in the complex final reporting layer where mistakes matter most.

Customer testimonialOriginal

Customer outcomes