Welcome back to the Maia New Features Blog! This week's changelog updates bring several major updates designed to enhance pipeline flexibility, improve collaboration, and make your experience with Maia AI Agents smoother than ever. Let’s dive into the details.

🤖 New Mission Control features

Mission Control just got even more efficient! This week’s updates help you to keep your work moving at pace, while ensuring you stay informed about all the tasks Maia AI Agents are working on.

🔔 Slack notifications

You can now get a Slack alert as soon as Maia AI Agents need your help–no need to keep Mission Control open to monitor their progress.

A task moves to the Needs Attention column of your Mission Control board when Maia AI Agents stop–because they’ve finished their task, they need you to approve a tool action, or they’re waiting on input from you. With Slack notifications, you’re in the loop as soon as they need your attention, enabling you to respond quickly and keep things moving.

To set up alerts, click Slack notifications in Mission Control, toggle notifications on, and enter a Slack incoming webhook URL. You’ll see a checkmark next to the notifications icon when they’re active. Pause and resume notifications at any time using the toggle.

Ready to get started? Read our guide to Slack notifications for Mission Control.

🎯 New Balanced permission level

We've introduced a new Balanced permission level for Mission Control that lets Maia AI Agents move faster on the safe stuff while still checking in before making any big decisions

You can now choose between three preset permission levels when giving Maia AI Agents a task:

• Go with Ask permission if you want full control over Maia AI Agents’ work–they’ll ask for permission to do anything beyond reading and editing files.
• Choose Balanced to let Maia AI Agents get on with recoverable work on their own, while still stopping to ask when it really matters.
• Pick Full access when you’re giving Maia AI Agents trusted, hands-off tasks, such as prototyping or work in a sandbox environment.

For more details about all the permission levels in Mission Control, read Permission levels.

🔄 Maia AI Agents support shared pipelines

When you ask Maia AI Agents to build a new orchestration pipeline, whether in Designer or Mission Control, they now find and use suitable shared pipelines, instead of rebuilding the same thing from scratch.

If there's a clear match, Maia AI Agents will simply use a Run Shared Pipeline component to use the available pipeline. If there are multiple candidates, they’ll ask you to choose which one to use. And of course, if Maia AI Agents can’t find a matching shared pipeline, they’ll get started building your new pipeline as usual!

For more information, read the Orchestration pipelines section of our guide to building pipelines with Maia AI Agents.

🔎 Enhanced usage and billing insights

We’ve updated the usage dashboard and released credit budgets to give your teams more detailed information than ever before about your credit consumption and usage. These features are available for users with the Manage Billing permission.

📊 Dive into your usage dashboard

We've made significant upgrades to your usage dashboard to provide deeper visibility into where your credits are being spent. The usage dashboard now features:

• Flexible date ranges: View consumption over preset ranges (last 7 days, last 30 days, monthly, quarterly), or select a custom range.
• Consumption overview graph: See your remaining credits and the credits you’ve used this billing period at a glance.
• Feature-level breakdown: Toggle between credit breakdowns by orchestration, transformation, and additional users, each showing the total credits used and their percentage of your total consumption.
• Project and pipeline breakdown: Filter by project, environment, and feature, then use the sort and search options, to see credit usage at the individual pipeline level.
• Daily breakdown: Drill down into any pipeline or user's consumption on a day-by-day basis.

Check out the Usage dashboard documentation to learn more.

💰 Budgets and alerts

You can now create budgets and set credit usage thresholds to monitor your credit consumption and receive an alert when you approach or exceed your allowance.

You can set two types of budget:

• Global budget: Track your total credit consumption across every project in your account, scoped to your current contract period.
• Project-level budgets: Set a credit consumption limit for one or more individual projects and track their consumption.

For each of your budgets, you can set one or two usage thresholds as percentages of the corresponding credit consumption limit. Then, set up billing notifications to receive an alert by Email, Slack, or Webhook when your usage exceeds any of these thresholds.

Budgets and thresholds are informational only–they don't restrict usage. For more information, read Budgets and alerts and Billing notifications.

💬 We'd love to hear from you!

Let us know how these new features are improving your workflows — we're all ears! Feel free to add any comments or questions below.

Welcome back to the Maia New Features Blog! This week, we're excited to bring you updates that give you greater control and visibility over your pipeline operations. We've introduced enhanced status tracking so you can see exactly what's happening with your pipeline steps, plus new concurrency controls for iterators to help you optimize performance. For a full list of recent changes, be sure to check our changelog updates.

🚦 New “Pending” status for pipelines

When checking a pipeline’s status using your pipeline run history, task history, or the Maia API, you can now see the difference between a pipeline step that's actively executing and one that's waiting for a runner slot.

Steps will only show as Running when they're actively executing. Before that point, they'll show as Pending, so you'll always know whether something is genuinely in flight or just waiting. As tasks are picked up, pending tasks move to running in real time. This makes it easier to diagnose whether a slowdown was a real execution issue or just queue pressure.

Read the documentation to learn more about viewing step execution status.

🔁 Maximum concurrency limits for iterators

You can now set a maximum number of concurrent iterations on any iterator in Maia, giving you more flexible control over how pipelines are executed. This allows you to:

• Control concurrency: Previously, you had to choose between full concurrency of the available runner capacity or fully sequential runs. Now you can set a sensible concurrency level that gives you optimal performance without overwhelming your downstream systems or data warehouse.
• Import Matillion ETL pipelines with sensible defaults: Apply a sensible max concurrent iterations when importing pipelines, ensuring there are no unintended consequences of Maia’s greater scalability.

For customers upgrading from Matillion TL to Maia specifically, we are introducing a default of 16 when importing a pipeline into Maia. You can be change this setting or completely turn off the limit when setting your import preferences.

⚠️ Watch out for iterator stacking—limits are multiplicative, not additive. Stacked iterators can hit full runner capacity quickly if not configured carefully.

💬 We'd love to hear from you!

Let us know how these new features are improving your workflows—we're all ears! Feel free to add any comments or questions below.

Want to get involved?

Join the Matillion Community to stay up to date, share feedback, and help shape our product roadmap for future innovations.

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Welcome back to the Maia New Features Blog! This week brings some exciting updates to streamline your data workflows and boost productivity. We've launched Google BigQuery integration for Maia, introduced bulk variable management capabilities, and enhanced the Designer command palette. See our changelog updates for all the details.

📣 Google BigQuery on Maia is now live

We're excited to announce that Google BigQuery is now supported in Maia! This powerful addition to our platform brings enterprise-grade data warehousing capabilities directly to Maia users.

With this integration, you can now seamlessly connect your Google Cloud data warehouse to Maia's comprehensive data platform, enabling faster analytics and more efficient data processing workflows. This expands Maia’s capabilities, giving you access to Google BigQuery's scalable infrastructure while using Maia AI Agents for intelligent data operations.

To learn more, read our guides on Google BigQuery projects and Google BigQuery environments. Then check out our Full SaaS and Hybrid SaaS setup guides to get started.

📤 Export and import your variables between pipelines and projects

Managing variables across multiple pipelines and projects just became much more efficient! You can now bulk export and import variables using a convenient JSON file format.

This feature lets you select specific variables to export from your project and pipeline, then import them wherever needed. When importing, Maia clearly shows you which variables are new and which will be updated, giving you complete visibility and control over the process. Your existing environment-specific values and permissions are preserved throughout.

This is particularly valuable when modularizing pipelines or sharing variables across multiple projects, removing the need to manually recreate variables one by one. For more information, read Export and import variables.

🎯 Enhanced command palette for faster Designer workflows

The Designer command palette has been expanded to provide quick access to a much wider range of actions. Press Cmd+Shift+K or Ctrl+Shift+K while on the Designer canvas to perform Git actions, open Designer tabs and panels, create and manage pipelines, schedule a pipeline, and perform many more quick-access actions.

The command palette learns from your usage patterns, and will suggest your most frequently used commands first. The smart search finds what you need even if you don't spell action names exactly, and new Designer capabilities will automatically appear in the palette as they're added.

This removes the need to navigate through multiple menus for common tasks, keeping your hands on the keyboard and your workflow uninterrupted.

💬 We'd love to hear from you!

Let us know how these new features are improving your workflows—we're all ears! Feel free to add any comments or questions below.

Want to get involved? Join the Matillion Community to stay up to date, share feedback, and help shape our product roadmap for future innovations.

Welcome back to the Maia New Features Blog! This week, we're bringing you proactive pipeline anomaly detection, better iterator visibility, and GitLab API support, all designed to give you greater control and insight into your workflows. For a full list of recent changes, be sure to check our changelog updates.

⏱️ Monitor pipeline run duration with new anomaly alerts

Maia now provides early warning alerts when your pipelines take longer or shorter than expected to complete, helping you catch performance issues before they impact your business operations.

For every scheduled or API pipeline run, Maia compares the duration against its historical baseline and fires an anomaly alert if it falls outside the statistically normal range. You'll receive two types of alerts:

• Run is taking longer than expected: Fires mid-run, so if a pipeline is hanging, you find out while it's happening, not after a timeout.
• Run finished unusually quickly: Detected at completion, useful for identifying unexpected data volume drops or processing being skipped silently.

Alerts include the actual duration, the expected range, and how far outside it the run fell, making them immediately actionable. Learn more about pipeline duration anomaly alerts in our documentation

🔄 See iterator variable names and values in task history

We've made a valuable improvement to all iterators in Maia – the new "Record values in task history" parameter allows you to print the names and values of variables used in each iteration directly in the task history tab in Designer and in the Observability dashboard.

This gives you better visibility into your pipeline execution, making it easier to debug and monitor iterator performance. You'll now have clear insight into exactly what variables are being processed during each iteration cycle.

🔗 GitLab repositories now supported via the API

You can now associate a GitLab repository to a project directly through Maia's public API, eliminating the need to use the UI for project creation.

Previously, the Project Provisioning API endpoints only supported GitHub and Azure DevOps. With this expansion, you have more flexibility in how you manage your version control integration with Maia.

Read the documentation for detailed setup instructions.

💬 We'd love to hear from you!

Let us know how these new features are improving your workflows—we're all ears! Feel free to add any comments or questions below.

Want to get involved?

Join the Matillion Community to stay up to date, share feedback, and help shape our product roadmap for future innovations.

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Welcome back to the Maia New Features Blog! This week, we're bringing you enhanced pipeline monitoring and control capabilities. We've expanded notification options beyond just failures and introduced new system variables to give you better visibility into your Iterator components. For a full list of recent changes, check our changelog updates.

🔔 Additional pipeline notification triggers

You can now subscribe to completion alerts for any pipeline state, not just failures. When adding a notification, you can now also choose to be alerted when pipelines are successful, canceled, and skipped.

Mix and match your notification triggers per project or environment, and choose how to receive them by email, Slack, or Webhook. This provides more flexibility for teams who want confirmation that critical pipelines are running successfully, or need to react to cancellations and skips.

Check out our Pipeline notifications guide to get started.

🔄 Iterator component-specific system variables

We've added three new component-specific system variables for iterator components to give you better visibility and control over your pipeline iterations:

• .thisComponent.iterationsAttempted counts the number of attempted iterations
• .thisComponent.iterationsGenerated counts the number of started iterations, counting both successful and failed iterations
• .thisComponent.iterationsSuccessful counts the number of successfully completed iterations

This gives you more granular monitoring for your iterator components, helping you troubleshoot and optimize your pipeline performance. Read Component-specific system variables in our documentation to learn more.

💬 We'd love to hear from you!

Let us know how these new features are improving your workflows—we're all ears! Feel free to add any comments or questions below.

Want to get involved?

Join the Matillion Community to stay up to date, share feedback, and help shape our product roadmap for future innovations.

Welcome back to the Maia New Features Blog! This week, we're thrilled to announce the public preview launch of Mission Control and Context Engine—two major new capabilities that transform how you manage AI agent tasks and ground Maia AI Agents in your business data. For a full list of changes this week, check out our changelog updates.

🗺️ Context Engine: give Maia AI Agents a living map of your data

Context Engine is now in public preview! This powerful new feature enables you to builds knowledge graphs—a living map of the business logic, entities, and relationships in your data landscape—so Maia AI Agents can generate accurate, production-ready pipelines that speak the language of your business.

Maia AI Agents are only as good as their understanding of your data and your business. Out of the box, they know the shape of a warehouse, but not what the tables mean, how concepts relate, or which data is trustworthy. Context Engine closes that gap by crawling your warehouse, inferring the business entities behind your schemas, and storing them as a semantic graph that Maia AI Agents can draw on. The result is less hand-holding, fewer wrong guesses, and pipelines that match how your organization actually thinks about its data.

What's new:

• Domain-focused knowledge graphs: Create a graph per domain (Finance, Sales, Marketing...). Keeping each graph focused helps Maia AI Agents learn the language and logic of that data far more effectively.
• Automated crawlers: Attach a crawler to a warehouse connection and it harvests physical assets and infers the business concepts behind them, keeping the graph accurate and in sync. Works across Snowflake, Databricks, and Amazon Redshift.
• Pipeline execution crawls: Bring in runtime lineage and execution history so Maia AI Agents can reason about what's fresh, what's stale, and how data actually flows.
• Scheduling: Run crawlers on a standard interval or an advanced cron schedule, with pause/resume controls.
• Access controls: Choose Public (every project) or Restricted (project allowlist) per graph, and manage who can view or manage each graph at the user level.

Read the docs to get started.

🎯 Mission Control is now in public preview

We're excited to introduce Mission Control—a centralized hub to launch, monitor, and review the work your Maia AI Agents are doing for you. Available now in public preview, Mission Control also introduces two new capabilities: multi-modal chat and “bypass permissions” mode.

Until now, managing Maia work meant staying within a single conversation. Mission Control transforms this experience by providing a kanban-board-level view of everything Maia AI Agents are doing across your projects, enabling you to run multiple tasks in parallel and only intervene when needed.

Key features:

• Kanban board: Every task flows through Backlog → In Progress → Needs Attention → Completed for at-a-glance status tracking.
• Quick task launch: Select a project, branch (or create a fresh isolated working branch), environment, and optional knowledge graph, then describe your requirements.
• Auto-start capability: Tasks begin processing automatically when created—no manual intervention required.
• Live conversation panel: Monitor real-time progress and send follow-up messages without leaving the board.
• Needs Attention column: Tasks requiring your review are clearly surfaced in their own dedicated space.
• Seamless review workflow: Jump to Review in Designer to inspect changes, then move to completed when satisfied.
• Advanced filtering: Sort by project, source, and time period, or search across all tasks.

📎 Multi-modal chat

You can now attach images and PDFs directly to your task prompt in Mission Control. Give Maia AI Agents a supporting diagram of the pipeline you want built, a screenshot of an error you're hitting, or a PDF containing the spec from your team—and they can work straight from the source instead of from your description of it.

• Attach images: Drop in a supporting diagram, screenshot, mockup, or whiteboard photo—perfect for pipeline diagrams or system designs you'd otherwise have to describe in words.
• Attach PDFs: Share a spec, requirements doc, or report you want Maia AI Agents to use as context for the task.

Use the attach (+) control in the prompt area to add an image or PDF to your message.

🔓 Bypass permissions mode

Bypass permissions mode is the opposite of Ask permission mode. Tool calls execute immediately, with no approvals, decisions, or check-ins—great for trusted, hands-off runs like prototyping or clearing a backlog in a sandbox. Under the hood it's the same as approving every permission prompt as it comes up; Maia AI Agents aren't unlocking new capabilities, only skipping the checkpoints.

We don't recommend leaving Bypass permissions on by default. Ask permission should be your normal mode. Flip to Bypass for specific tasks where you know what Maia AI Agents are doing and you've scoped the environment for it. Use it in safe, well-scoped environments:

• A disposable project or branch where unintended changes are easy to throw away (scratch branch, dev environment, sandbox project)
• A warehouse user/role with only the access Maia AI Agents need. Point them at a dev warehouse or a least-privilege role, not your production admin credentials
• Approval gates on when Maia AI Agents are working from untrusted input like a PDF or image you didn't author

Mission Control is currently user-scoped, meaning you'll only see your own tasks.

You can access Mission Control through the AI Agents icon in the left navigation. Click + Add task to launch your first task. Any tasks requiring your input will appear in the Needs Attention column.

Read the docs to get started.

💬 We'd love to hear from you!

Let us know how these new features are improving your workflows—we're all ears! Feel free to add any comments or questions below.

Want to get involved?

Join the Matillion Community to stay up to date, share feedback, and help shape our product roadmap for future innovations.

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