WHAT'S NEW WITH MAIA  ·  SPRING 2026

Maia is the data team that runs in your architecture.

Four capabilities have launched. Maia now knows your naming conventions, architecture standards, migration backlog, and team’s exact patterns.
KEYNOTE

CEO keynote

From AI copilots to AI-executed production data engineering.

Discover why making the existing model of data engineering faster isn't the answer, and what changes when the system itself takes on the work, end-to-end, at scale. Our CEO, Matthew Scullion, speaks on the paradigm shift behind Maia, and what it means for your migration backlog and AI roadmap.
Book a demo
Connect with Matthew

Capabilities launched

1. Mission Control

Manage every Maia job from a single Kanban board, the control plane for your agentic data team.

2. Context Engine

Learns your environment, naming conventions, data contracts, and keeps learning as your stack evolves.
Learn More

3. Skills & Planning

Encode your team's patterns and show the build plan before a line of code.

4. Migration Agents

Rebuild your Informatica, Alteryx, SSIS, Talend, and Qlik estate natively in Snowflake, Databricks, or AWS.
Learn More

1. Mission Control

Manage every Maia job from a single Kanban board, the control plane for your agentic data team.

2. Context Engine

Learns your environment, naming conventions, data contracts, and keeps learning as your stack evolves.
Learn More

3. Skills & Planning

Encode your team's patterns and show the build plan before a line of code.

4. Migration Agents

Rebuild your Informatica, Alteryx, SSIS, Talend, and Qlik estate natively in Snowflake, Databricks, or AWS.
Learn More
Attending Snowflake Summit?
Get hands-on with all of these capabilities at Booth #2603.
Learn more
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Most AI data tools generate code. Maia runs your data engineering.

Mission Control, Context Engine, Skills & Planning, Migration Agents. Four capabilities pointing in one direction: Maia learns your environment continuously, plans before it builds, runs migrations, new builds, and quality fixes in parallel. Maia remembers and ships every pipeline in your architecture by default. Production-grade isn't a future feature. It's what shipped this spring.
With Maia, you can say yes to every AI initiative on the roadmap, without adding a single headcount.

Live demos

Overview

Meet your new AI data team

- See what changes when AI moves from assistance to autonomous execution
- Watch Maia plan structured work and apply your team's patterns through Skills
- Learn the Reverse Prompt: how Maia asks for business context before it builds
Mission Control

The catch before the dashboard breaks

- Maia spots a null-value spike in a Lead_Score field before bad rows hit a dashboard
- Context Engine understands downstream use, so it pauses, raises a ticket, and proposes the fix
- The Data Manager reviews, approves, and Maia implements
CUSTOM CONNECTORS

A custom connector for a homegrown app

- Maia takes the internal API docs for a tool with no off-the-shelf connector
- Context Engine guides Maia to generate the connector and a business-specific test framework
- Tests run against your real schemas, naming conventions, and regional compliance rules
MISSION CONTROL

The whole estate, running in parallel

- Mission Control runs every migration, pipeline build, quality fix, and Reverse ETL job on one Kanban board
- Maia plans the work, surfaces it for approval, executes, and reports back
- Maia handles execution. Your team handles the decisions
Overview

Meet your new AI data team

- See what changes when AI moves from assistance to autonomous execution
- Watch Maia plan structured work and apply your team's patterns through Skills
- Learn the Reverse Prompt: how Maia asks for business context before it builds
Mission Control

The catch before the dashboard breaks

- Maia spots a null-value spike in a Lead_Score field before bad rows hit a dashboard
- Context Engine understands downstream use, so it pauses, raises a ticket, and proposes the fix
- The Data Manager reviews, approves, and Maia implements
CUSTOM CONNECTORS

A custom connector for a homegrown app

- Maia takes the internal API docs for a tool with no off-the-shelf connector
- Context Engine guides Maia to generate the connector and a business-specific test framework
- Tests run against your real schemas, naming conventions, and regional compliance rules
MISSION CONTROL

The whole estate, running in parallel

- Mission Control runs every migration, pipeline build, quality fix, and Reverse ETL job on one Kanban board
- Maia plans the work, surfaces it for approval, executes, and reports back
- Maia handles execution. Your team handles the decisions
SOPHOS

Making AI delivery predictable at enterprise scale

Sophos CDAO on taking a pipeline task from 5 days to 30 minutes, an 80× improvement, and what it takes to make AI execution dependable at enterprise scale.

By the numbers

6 min
Per-pipeline migration, down from 1 week
Balfour Beatty · Mark Hume
1,300%
Efficiency gain in sentiment analysis operations
St. James’s Place
40,000
Human hours saved, 11 years of FTE effort
St. James’s Place · Kelly Maggs
$100K
Saved in consultancy & services spend
Edmund Optics
85%
Faster than manual migration rewrite
Partner case study · March 2026
“Maia makes the impossible, possible. We'd almost given up hope, this has given us a new hope that we can shortcut that process.”
Mark Hume
Head of Data, Balfour Beatty
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What's in it for your team

Four releases. Four operational shifts. Here's what Maia changes for your team.

From

  • Every pipeline manually reviewed against your standards, and only when reviewers have time
  • 18-month migration backlogs and six-figure annual budgets locked in Informatica licenses
  • Every AI tool re-prompted with your architecture, and watching it forget by the next session
  • Engineers babysitting pipelines, hunting failures, and sitting in status meeting.

To

  • Context Engine encodes your institutional and tribal knowledge. Every pipeline ships your way by default
  • Migration Agents read Informatica, Alteryx, SSIS, Talend, Qlik, and rebuild them natively in Snowflake, Databricks, Redshift, or BigQuery. Balfour Beatty: 1 week per pipeline → 6 minutes
  • Skills learn how your team works. Planning shows the build before a line of code. Maia remembers your environment forever
  • Mission Control puts every job on one Kanban board. Maia plans, surfaces work for approval, executes, and reports back. Your team manages outcomes, not tasks

See Maia work for
your architecture

Ready to move from generic pipelines to yours? Talk to the team.
Book a personalized demo
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