Collibra

11/03/2026

Last month, we welcomed trail to Collibra. Here’s why we’re so excited about what this acquisition unlocks. 🚀

Anyone who’s built an AI agent in a day and then waited months for compliance to sign off knows how frustrating that wait can be. With trail, our customers can finally shorten it.

Governance work that used to mean chasing evidence and filling out assessments now happens automatically, and stays current as systems change. Once an agent is live, runtime controls make sure it only uses the tools and data it’s supposed to, so teams can ship AI with confidence instead of crossing their fingers.

And because it all runs on the context our AI Command Center already holds about your AI, your data and your owners, the right controls show up for the right systems without anyone starting from scratch.

Faster approvals, fewer surprises and people still in charge of the big decisions.

Learn more: https://ow.ly/kGpz5101MFM

11/02/2026

Are your employees becoming AI babysitters?

Agents were meant to free people up. Without reliable business context, humans end up checking and correcting their work instead.

Our CEO Felix Van de Maele calls it the 'hallucination tax.' As he tells Inc. Magazine: "You can manually review the output of a handful of agents, but that approach doesn't scale when you're deploying them across an organization."

The models are capable, but they need the right context and controls behind them.

Read the full piece from Netta Jenkins: https://ow.ly/WNa65102Wlb

AI agents promised to eliminate busywork, but unreliable outputs and weak data foundations are creating a hidden productivity cost.

10/30/2026

October’s product updates are here, and our latest release gives you more visibility, more choice and more control.

🔹 Operational Trust for AI agents: A dynamic AI Trust Score for every deployed agent, plus AIUC-1 certification status and token trends. It covers Databricks Agent Bricks, Microsoft Foundry, Amazon Bedrock and Google Gemini in one dashboard.

🔹 Bring Your Own Model: Run Maestro’s AI features on your own model, starting with Google Gemini Enterprise. It’s trained on your data and helps you avoid another compliance review.

🔹 Bring Your Own Continuous Deployment: Deploy and upgrade Collibra Edge through tools like Argo CD. Config lives in Git, upgrades follow your approval process and Edge needs fewer Kubernetes permissions.

🔹 SAP S/4HANA integration: Bring your ERP tables, columns and schemas into the catalog, so the data behind your financial reporting is searchable, owned and certified.

Trust your agents continuously, choose the models behind them and run Collibra your way.

▶️ Watch the full walkthrough with Michael Rahm and learn more here: https://ow.ly/QW7q5102efn

10/29/2026

Bring your toughest questions to our Ask Me Anything session with Databricks.

We’ll start with a live demo on how to keep your data trusted as it moves into AI applications, from governing operational data in Databricks Lakebase to making Unity Catalog’s AI Gateway and Genie safe to use at scale. Then it’s your turn to ask subject matter experts anything you want.

Secure your spot on November 18: https://ow.ly/FvYx5101QY6

10/28/2026

🏆 We’re proud to announce the winners of the 2026 Collibra Customer Excellence Awards!

Since 2018, these awards have celebrated the teams and individuals who trust Collibra to unify governance across every data source, use case and user. Thank you for your vision and commitment to showing what’s possible when organizations put trusted data and AI to work.

🌐 Data Program of the Year: Siemens AG
🧑‍💼 Data Citizen of the Year: Tina Keller Florcke, Salt River Project
🚀 Acceleration All-Star: PwC
✨ Trendsetter: Macy's
🤠 Collibra Ranger of the Year: Umit Bhargava, Gallagher
🤝 Collibra Community Champion of the Year: Doug Berman, Stanford University
💡 Adoption Hero: A leading U.S. insurance provider

Congratulations to this year’s winners! https://ow.ly/eGmB5101Glx

10/27/2026

Your AI agents know a lot. That doesn't mean they understand your business.

They don't know what "customer" means at your company, which revenue metric is real or what data they're allowed to touch. A human would stop and ask, but an agent just guesses.

That guess is what we call the 'hallucination tax'. It shows up as wasted tokens, discarded outputs and endless manual reviews until leadership asks why the AI program is bleeding money.

At 5 agents, it's annoying. At 50, it's why the project gets canceled.

The fix requires governing the context layer across your entire stack, built directly into the foundation so agents get trusted data every time.

Read our new ebook, "The Missing Layer: Why context governance decides whether AI agents scale," for the framework to close that gap: https://ow.ly/iGXQ51018mo

10/26/2026

Among organizations with $100M+ in revenue, 96% say the root cause of failed AI initiatives almost always traces back to poor data foundations.

Scale was supposed to be the advantage. Instead, our latest research with The Harris Poll shows it's amplifying the problem most leaders assumed they'd already solved.

If you're leading AI at scale, you'll want to take a look at this. https://ow.ly/kr9G50ZZjtf

10/23/2026

London brought ambitious conversations and big ideas on governing AI at scale.

At the Collibra AI Summit, our CEO Felix Van de Maele welcomed data and AI leaders from across the UK and Europe to talk about what it really takes to trust AI in production, from clear visibility and accountability to governance that keeps pace with every agent.

Too often, ROI stalls because agents don’t know what your data means and no one can see what they’re doing. Collibra closes both gaps with governed context and control working as one system, so AI delivers value instead of rework.

Thank you, London. Watch the recap 👇

10/22/2026

Want trustworthy AI? Build the data foundation first.

Our co-founder Stijn asked Ulysses Demos, Head of Data Management and Protection Office at Red Sea Global, where teams should focus.

His advice is to build traceability early and take as long as you need, because everything else sits on top of it.

That way, when people questioned a new function or its return on investment, Ulysses could trace it back to a regulatory, legal or business requirement. Business requirements had to show ROI, which made those conversations much easier.

Hear how Red Sea Global moved past manual compliance to get ready for AI at enterprise scale: https://ow.ly/g94M50ZZ6gv

10/21/2026

Our CEO Felix Van De Maele recently asked a room full of data and AI leaders: "How many AI agents do you have in production? And what are they doing?"

Most couldn't answer either question.

That's where the industry is right now. Companies are encouraging teams to build and experiment, but no one is keeping count, and you can't govern what you don't know you have. Managing five agents is a staffing problem but managing a thousand is a systems problem, and you can't hire your way out of it.

Felix dug into this with Matt Marshall at VentureBeat's AI Week in New York. Better models won't solve it. Ask for your company's revenue and there's only one right answer, but agents miss it when they don't understand the business behind the data. Trusted AI at scale means knowing what you have, enforcing rules at runtime and keeping context accurate as the business changes.

We've spent two decades helping enterprises do this for data. Now we're doing it for agents.

Read more from Venturebeat: https://ow.ly/Htf150ZZtIQ

As AI agent fleets grow, enterprises need inventory, enforceable contracts and maintained business context to control risk, cost and reliability.