Rik Van Bruggen

I warmly invite you to watch this short clip - it so positively articulates what we as #devrevelers have been working on - it's amazing to be part of this journey.

Computer WORKS hanks to deep integrations (#airsync) with existing structured AND unstructured data (computer #memory) and sophisticated orchestration and analytics functions that underpin productive #ai.

YouTube video by DevRev Meet Computer, by DevRev

Yesterday, late afternoon CET, DevRev announced Computer - your AI teammate. Always there, always helping, always aware of everything that goes on in your business

Meet Computer, Your AI Teammate for Teams | DevRev Discover Computer by DevRev – AI that unifies teams, automates tasks, and resolves 85% of customer issues. Beta launched September 9, 2025.

Here's your personal invitation from
@dpessential.bsky.social
to join to #teamintelligence era. Where
Computer acts (not just summarizes), as a teammate (not a tool), for every team, always and everywhere.
devrev.ai/blog/meet-co...

Last week I wrote a short article about the synergies between #knowledgegraphs and #ai, and the way #devrev solves for that in our platform. Of course, I wanted to try to explain and summarize that "graph"-ically. How does this look for a summary?

To Platform or Not: Making the smarter AI choice Point Solution or Scalable platform? Learn why platforms deliver long-term speed, flexibility, and growth—beyond single-use AI tools.

Take a look at the new @devrev blogpost that I just published: devrev.ai/blog/smarter... ... as always - I would love to hear your thoughts!

To Platform or Not: Making the smarter AI choice Point Solution or Scalable platform? Learn why platforms deliver long-term speed, flexibility, and growth—beyond single-use AI tools.

Do I buy something off the shelf?
Or develop everything from scratch?
Or, maybe, just maybe, could it be that there is a middle ground - and that you can buy a platform upon which you can build FASTER?

To Platform or Not: Making the smarter AI choice Point Solution or Scalable platform? Learn why platforms deliver long-term speed, flexibility, and growth—beyond single-use AI tools.

I wrote some ideas about a "classic" IT problem that I think is popping up more and more in the #agentic #ai world: how to go about developing these solutions for my business.

DevRev x FOSSA case study | DevRev Growing fast created growing pains. FOSSA’s teams were spread across scattered tools, with slow processes and siloed visibility holding them back. Support felt reactive, engineering lacked context, and customers noticed the gaps. To keep scaling, something had to change. That’s when they turned to a single AI-powered system that brought support, engineering, and success together. With workflows clicking into place and real-time visibility across teams, FOSSA shifted from reactive to proactive and built a support experience ready to scale: https://dvrv.ai/475klgE #DevRev

Take a look at this post: https://www.linkedin.com/posts/devrev_devrev-x-fossa-case-study-activity-7363910205237088258-w3tc - Fossa achieved impressive, *measurable* results with DevRev - and you could do the same.

LinkedIn Pulse

Just published a short article about the synergies between #knowledgegraphs and #ai - rooted in my experience at DevRev in the past few montsh. See www.linkedin.com/pulse/ai-wit... - would love to hear your thoughts!

This article also reminded me of an old distributed systems discussion that I learned in my uni days - how distributed "sync"(chronous) systems are so hard to get working at scale, and how "async" systems are conceptually harder, but much more resilient.

Synchronous and Asynchronous AI agents: Which one's better for your businesses ? Discover the key difference between Synchronous and Asynchronous AI agents. Learn how each model impacts the scalability and efficiency of the businesses.

I got the chance to write another short blogpost on the #devrev website about how #ai #agents can take different forms - eg. synchronous vs asynchronous - and how your business needs a platform that supports them all - read it on devrev.ai/blog/case-as...

Unlocking operational efficiency with DevRev Search · Zoom · Luma Information overload and tool sprawl are quietly killing operational efficiency across enterprises. According to McKinsey, employees spend up to 25% of their…

Join us by registering over here lu.ma/x2n8bn33 - it's will be a great event.

Unlocking operational efficiency with DevRev Search · Zoom · Luma Information overload and tool sprawl are quietly killing operational efficiency across enterprises. According to McKinsey, employees spend up to 25% of their…

So how do you make that tangible? How to you explain that? Well, as usual, *show*, don't tell, is the better method. And that's what Sunil and Richard are going to be doing during our webinar next week.

Unlocking operational efficiency with DevRev Search · Zoom · Luma Information overload and tool sprawl are quietly killing operational efficiency across enterprises. According to McKinsey, employees spend up to 25% of their…

At #DevRev, I have found so many interesting ideas and topics that drive me, and our team, forward. #ETL, #knowledgegraphs and #AI #agents are of course the three core ones, but even more importantly it's the fact that we can truly help clients become more operationally efficient - now!

Why Structured Systems Beat Documents for Enterprise Automation Discover why structured systems—not static documents—are essential for scaling enterprise-grade automation. Learn how to drive efficiency, accuracy, and speed.

Achievement unlocked!
I just published my first #blogpost on the #devrev blog. It's about how, in order to be truly productive, #ai #agents will need both #structured and #unstructured data. Read it over here devrev.ai/blog/structu... and let me know what you think!

Amazing #learn and #lead event by #devrev in #amsterdam. First giving context and info, and soon we go into a #handson #workshop.

Why Layers Matter in Agentic AI systems A blog about my work and fun with Neo4j, the world's leading graph database platform.

Here's a short article that I wrote about why I think #devrev 's layered approach to building #agentic #ai systems is so cool. See blog.bruggen.com/2025/06/why-... or on LinkedIn... As always feedback welcome!

What's the best approach? In my view, both #build and #buy are dead: there's a happy medium between the two approaches, where you buy the core stack, and then customize that in detail. Hope you like the article. Ping me if you want to discuss.

Build vs. Buy: Reimagining AI-native Customer Experience (CX) Solutions for the Enterprise The Enterprise dilemma: Building vs. Buying AI-native CX solutions Enterprises face a critical decision when it comes to implementing AI-native CX solutions: should they build custom solutions from sc...

Over the weekend, I was reflecting on how customers build or buy #ai solutions. Should you #buildorbuy a technology these days? I thought I would write down some of my thoughts, and apply them to how #DevRev is using this approach today in the marketplace.
www.linkedin.com/pulse/build-...

Impedance Matching for DevRev Communicating what DevRev does is not trivial. The article discusses how different audiences will benefit from a different message tuned to them specifally.

I just wrote a post about #impedance #matching for #devrev. See www.linkedin.com/pulse/impeda... - hope it's useful.

Don't try these fallacies at home kids!
@jimdowling.bsky.social has a thing or two to say about building *production* #ai and #ml systems. Not your odd hobby project - but a true 24/7 system that you can rely on. That's why we do what we do at @hopsworks.bsky.social .

That, I promise, is not a small task. And that, I offer, is one of the main value drivers of the @hopsworks.bsky.social #AI #Lakehouse for our customers.

There's a lot of great "pieces of the puzzle" out there that you can just pick off the shelf, install in your environment, and get going. At least that's what it looks like, because you still need to *integrate* the different pieces, and then *keep them integrated* forever thereafter.

Hopsworks AI Lakehouse: The Power of Integrated MLOps Components - Hopsworks Discover how Hopsworks simplifies MLOps and streamlines feature management, model serving, and governance for scalable, cost-efficient AI solutions.

Here's a piece that I wrote about "Integrated MLOps Components". www.hopsworks.ai/post/hopswor...

Over the past year or so, I have found that customers often consider a build vs. buy question. And I understand them.

YouTube video by Hopsworks Show, don't tell - Building Data Pipelines with AI

This is very cool. Lex and Aleksey show you how you can use an #LLM #assistant to generate code that automatically imports features into the Hopsworks feature store. This makes getting started with the #ai #lakehouse even easier! See youtu.be/wtEPONdKV6Y for another great episode of #showdonttell.

The world of AI and data - how to build best-in-class AI solutions and mitigate risk This episode features Rik Van Bruggen, VP for EMEA at Hopsworks, a platform for Data-Intensive Artificial Intelligence, who unpicks the captivating and trending world of AI and Data. Find out what you...

I had a great time talking to the @ovhcloud.bsky.social team about how we at @hopsworks.bsky.social work together to make the #sovereign #ai and #ml cloud a reality together. Check it out on smartlink.ausha.co/supercharge-... or wherever you get your podcasts.

* focus their efforts on people and processes over technology and algorithms.
* have moved quickly to focus on GenAI, which opens opportunities in content creation, qualitative reasoning, and connecting other tools and platforms.

Pretty darn good summary, I think.

* invest strategically in a *few high-priority opportunities* to scale and maximize AI’s value.
* integrate AI in both cost reduction and revenue generation efforts.

* are more ambitious, setting big targets ($1 billion in productivity improvements at a financial institution, for example, or $1 billion in combined revenue increases and cost reductions at a biopharma firm) and investing in AI and workforce enablement.