Maia features🔗

This guide describes the capabilities available through Maia in Maia Foundation. It is intended for Matillion ETL users who want to understand what Maia offers before upgrading to Maia Foundation.

Maia is the agentic AI capability built into Maia Foundation. It operates inside Designer, where you can use natural language prompts to build pipelines, explore data, troubleshoot errors, and manage your project files.

Pipeline development🔗

Maia builds, runs, and manages both transformation and orchestration pipelines from the Maia chat interface in Designer. For more information, read Building data pipelines with Maia.

Transformation pipelines🔗

Describe a data transformation objective and Maia creates the pipeline for you. It adds the appropriate components—such as Table Input, Calculator, Filter, and Aggregate—connects them, and configures each one based on your description.

Example prompt: "Get sales data from the orders table, calculate revenue by region, and store the results in a new table called regional_revenue."

You can iterate on the pipeline within the same session using follow-up prompts such as "Add a margin column" or "Filter for US customers only."

Orchestration pipelines🔗

Maia builds orchestration workflows from high-level descriptions. Supported pipeline elements include connectors, actions, DDL operations, control logic (conditions and loops), iterators, and scalar variables. Maia prompts you for required details such as secrets or credentials as it builds.

Example prompt: "Extract sales data from Salesforce, transform it using the clean_sales pipeline, then load it into Snowflake."

Multi-pipeline workflows🔗

Maia understands cross-pipeline dependencies and can set up multiple pipelines to run in sequence. You can build and chain pipelines step by step from a single session, adding conditions, alerts, or post-processing steps as you go.

Running pipelines🔗

You can ask Maia to run any orchestration or transformation pipeline directly from the chat interface. Maia requests explicit permission before executing, then monitors the run and reports live status updates—including rows processed and any component errors.

Sampling data🔗

When building transformation pipelines, Maia can sample existing tables in your data warehouse to detect column names, data types, and structure. This helps Maia configure components more accurately. Only 10–20 rows are sampled, and sampled data is stored for 30 days. Maia always asks for permission before sampling.

Committing and pushing changes🔗

Maia can generate a commit message, commit your pipeline changes, and push them to your current branch in Designer. You must approve the action before it proceeds.

Data exploration and visualization🔗

Maia can query your data warehouse to explore tables, views, and schemas. It can also visualize sampled data directly in the chat interface as charts and graphs, using 10–20 sampled rows. These visualizations help you identify trends and patterns without running a full pipeline.

Project and file management🔗

Maia can search through all files in your project to find specific content, configurations, or pipeline patterns. You can also ask Maia to move, rename, copy, or delete files to maintain a clean project structure.

Pipeline analysis and optimization🔗

Maia can analyze and explain existing pipelines—their components, data flow, and logic—without making any changes. You can also ask Maia to identify configuration problems and suggest fixes, or recommend optimizations such as parallelization and component selection improvements.

Slash commands provide a standardized way to run common analysis tasks. Type / in the Maia chat interface to see the available commands.

Command	Task
`/document`	Generate a Markdown file with information about a specified pipeline, file, or directory.
`/explain`	Generate a brief explanation of a specified pipeline or concept.
`/fix`	Identify issues in a pipeline and present options to fix them. Maia does not apply changes until you approve.
`/multi-table-load`	Load multiple tables from a data source using incremental or full load.
`/notes`	Add notes to a pipeline on the Designer canvas.
`/optimize`	Suggest performance improvements. Maia does not apply changes until you approve.

Custom connector creation🔗

Maia automates the creation of custom connectors for any API that has publicly viewable documentation. This process requires no coding and replaces the manual API profile configuration in Matillion ETL.

You can provide Maia with either:

A link to the API documentation page
A PDF, YAML, or JSON file (5 MB limit)

Maia scans the documentation, identifies available endpoints, configures authentication, applies pagination, and sends test requests. You can review and edit the result in the Custom Connector workbench before saving.

For a step-by-step guide, read Create a custom connector with Maia.

Context files🔗

Context files are Markdown (.md) files stored in your project at .matillion/maia/rules/. Maia reads all context files with every prompt and uses them to apply your project's naming conventions, data standards, business rules, and connection information automatically—without requiring you to repeat these in every prompt.

Key constraints:

There is a 12,000-character limit across all context files in the .matillion/maia/rules/ directory.
You can store additional, more detailed context files elsewhere in your project and reference them from your main context file. These do not count toward the character limit.

You can create and edit context files using the Add context or Edit context buttons in the Maia chat interface, or via the Files panel in Designer.

For more information, read Customize Maia with context files.

Skills🔗

Skills are reusable instruction sets stored at .matillion/maia/skills/[skill name]/SKILL.md in your project. Unlike context files—which Maia always reads—Maia activates skills selectively based on how it interprets your prompt.

Skills can reference additional files such as template pipelines or SQL scripts stored in the same folder. You can create skills from the Skills drop-down in the Maia chat interface.

Once a skill is committed and pushed to your remote repository, other users in the same project can merge it into their branch.

For more information, read Maia skills.

Sessions and plan mode🔗

A session is a structured, ongoing interaction with Maia that persists across your current branch. Maia builds on prior messages within the session, providing more coherent responses across multiple prompts. Sessions are private to each user and are saved in conversation history when you switch branches.

Plan mode🔗

Plan mode lets you review Maia's proposed actions before it makes any changes to your pipeline. Enable the Plan mode toggle at the bottom of the Maia chat interface. Maia will present a step-by-step plan for your review and approval before acting.

Maia can also suggest switching to plan mode automatically if it determines your prompt is complex enough to require planning.

For more information, read Sessions and tools in Maia.

Troubleshooting and monitoring🔗

Root cause analysis🔗

When a pipeline fails, Maia analyzes the error and provides a plain-language summary of what went wrong, identifies the exact location of the failure, and suggests fixes. For scheduled or API-triggered pipeline failures, a Fix with Maia button appears in the Troubleshoot with Maia banner on the Pipeline run details page. Clicking it starts a guided recovery process on a new branch.

Anomaly detection🔗

Maia monitors your scheduled pipeline runs and flags significant deviations from expected execution times using statistical modeling. Anomalies appear as red arrows next to duration metrics in the Pipeline Runs dashboard, with tooltips describing the deviation.

For more information, read Troubleshoot pipelines with Maia.