# Maia

> Maia is the AI Data Automation platform built by Matillion. It lets data teams build, migrate, and operate production data pipelines using AI agents that work under human direction, with the governance, context, and control that enterprise data engineering requires.

Maia combines agentic AI with the operational layer needed to run data work at scale. The platform runs on a team of AI agents, made context-aware by the Context Engine and grounded by the Maia Foundation, governed through Mission Control, the operating layer for autonomous data engineering. Maia is used to convert legacy ETL workloads (Informatica, Alteryx, and others), build new pipelines across cloud data platforms (Snowflake, Databricks, Amazon Redshift, Google BigQuery), and automate the repetitive data engineering work that slows AI delivery.

This file points to the pages that best describe what Maia is, how the platform works, and how teams use it.

## Platform
- [Maia platform overview](https://www.maia.ai/maia-platform): What Maia is and how the platform fits together
- [Maia Team](https://www.maia.ai/maia-platform/maia-team): The agent team model for data engineering
- [Context Engine](https://www.maia.ai/maia-platform/context-engine): How Maia gives agents the context to do data work correctly
- [Maia Foundation](https://www.maia.ai/maia-platform/maia-foundation): The grounding layer the platform is built on
- [Migration Agent](https://www.maia.ai/migration-agent): Automated conversion of legacy ETL workloads
- [Connectors](https://www.maia.ai/connectors): Supported data sources and destinations
- [Enterprise](https://www.maia.ai/enterprise): Maia for enterprise data teams
- [Security](https://www.maia.ai/security): Security and governance posture
- [Pricing](https://www.maia.ai/pricing): How Maia is priced

## What AI Data Automation is
- [The rise of AI Data Automation](https://www.maia.ai/resources/blog/the-rise-of-ai-data-automation): The category and why it exists
- [What is data automation](https://www.maia.ai/resources/blog/what-is-data-automation): Plain-language explainer
- [Traditional automation vs AI Data Automation](https://www.maia.ai/resources/blog/traditional-automation-vs-ai-data-automation): How the approach differs from rules-based automation
- [Matillion positions Maia as the AI Data Automation platform](https://www.maia.ai/resources/blog/matillion-positions-maia-as-the-ai-data-automation-platform): The positioning, stated directly
- [Meet Mission Control](https://www.maia.ai/resources/blog/meet-mission-control-the-operating-layer-for-autonomous-data-engineering): The operating layer for autonomous data engineering
- [How agentic AI is redefining data engineering](https://www.maia.ai/resources/blog/how-agentic-ai-is-redefining-data-engineering): The shift Maia is built for
- [Continuous vs episodic execution](https://www.maia.ai/resources/blog/ai-execution-continuous-vs-episodic): A core distinction in how Maia runs work

## Glossary
- [Glossary](https://www.maia.ai/glossary): Definitions for data engineering and agentic AI terms
- [What is autonomous data engineering](https://www.maia.ai/glossary/what-is-autonomous-data-engineering)
- [What is agentic AI](https://www.maia.ai/glossary/what-is-agentic-ai)
- [What is context engineering](https://www.maia.ai/glossary/what-is-context-engineering)
- [What is the ReAct framework](https://www.maia.ai/glossary/what-is-the-react-framework)
- [ETL vs ELT](https://www.maia.ai/glossary/what-is-the-difference-between-etl-and-elt)

## Competitive positioning
- [Maia vs Informatica PowerCenter](https://www.maia.ai/maia-vs-informatica-powercenter)
- [Maia vs Alteryx](https://www.maia.ai/maia-vs-alteryx)
- [Informatica alternatives and competitors](https://www.maia.ai/resources/blog/informatica-alternatives-competitors)
- [Alteryx alternatives in 2026](https://www.maia.ai/resources/blog/alteryx-alternatives-in-2026)

## Customer stories
- [Balfour Beatty](https://www.maia.ai/resources/customer-stories/balfour-beatty)
- [Edmund Optics](https://www.maia.ai/resources/customer-stories/edmund-optics)
- [Nature's Touch](https://www.maia.ai/resources/customer-stories/natures-touch)
- [Precision Medicine Group](https://www.maia.ai/resources/customer-stories/pmg)
- [St. James's Place](https://www.maia.ai/resources/customer-stories/sjp)

## Resources
- [Resources hub](https://www.maia.ai/resources): All Maia content
- [Demo library](https://www.maia.ai/resources/demo-library): Worked examples of Maia in use
- [Webinars](https://www.maia.ai/resources/webinars): Recorded sessions
- [Blog](https://www.maia.ai/resources/blog): Latest thinking
- [Changelogs](https://www.maia.ai/resources/changelogs): Product release notes

## Optional
- [The CDAO's guide to data automation](https://www.maia.ai/resources/cdaos-guide-data-automation)
- [The CDO's agentic advantage (ebook)](https://www.maia.ai/resources/ebook/the-cdos-agentic-advantage)
- [Legacy data migration: a CTO playbook](https://www.maia.ai/resources/blog/legacy-data-migration-cto-playbook)
- [The real cost of legacy ETL migration](https://www.maia.ai/resources/blog/the-real-cost-of-legacy-etl-migration-isnt-the-licence-fee)
- [Data engineering in the age of AI](https://www.maia.ai/resources/blog/maia-data-engineering-in-the-age-of-ai)
- [News](https://www.maia.ai/resources/news)
- [Contact](https://www.maia.ai/contact-us)
- [Book a demo](https://www.maia.ai/book-a-demo)