How a 95-year-old Dutch company's radical transparency became an information bottleneck - and the solution that turned overload into advantage.

Andre Foken, Nedap's CTO inherited a leaders' dream: a 95-year-old tech company with radical transparency baked into its DNA. Information flowed freely. Everyone contributed to decisions. The culture thrived.

Since 2019, Nedap had been using Slite to centralize their knowledge. In fact, Slite worked really well until... growth hit.

As Nedap's healthcare division ballooned from 150 to nearly 400 employees, everyone added docs to Slite, with their own nomenclature and taxonomy. Slite started to become useful.

"Some people were planning their mornings just to try and catch up, and it didn't work anymore. We have a culture where we want everybody to interact, but having gaps in your knowledge prevents you from contributing to discussions you might actually care about."

The challenge wasn't documentation. Nedap had mastered that years ago.

The challenge was discovery: how do you find the right information, in context, when you need it most?

The homegrown experiment

As a technology company with an AI mandate, Nedap tried building their own solution.

André's team created a custom GPT connected to their Slite documentation when ChatGPT launched. It worked well, but hallucinated a lot. It would confidently provide wrong answers about basic company policies.

Enter Super.

"The first thing that impressed me about Super was that it actually gives a sourced answer. But the biggest change was when it said 'I don't know.' Previous solutions always knew something. They were never right, but they were fully convinced. That 'I don't know' response was the biggest breakthrough."

Since Nedap was already a long-term Slite user, Super felt like natural evolution rather than disruptive change. As André remembers it: "It magically appeared in Slite at some point, and it just worked for us."

Super in action

Everything, everywhere, indexed

André's approach was characteristically direct: "We attached everything that we have and pumped as much information in there."

Nedap's Super instance now indexes content from Slack, Slite, GitHub, Confluence, Notion, Jira, HubSpot, SharePoint, and several custom internal systems including their decision tracker and intranet portals.

All the sources, still, weren't enough. So they built their own custom sources for Super

And of course, [I like] the variety of sources, but also the option to add our own custom stuff. Because we cannot expect you guys to always add every specific source. We also feed that into Super which is great because then, it can combine all of these things together.

Super knows the language

For a multinational company where English is the primary language but teams speak Dutch, Spanish, Polish, and Ukrainian, Super's multilingual capabilities proved unexpectedly valuable.

"You can ask your question in Dutch and get an answer, even though all the documents are usually written in English. Sometimes meeting notes will be in Dutch because the meeting was conducted in Dutch, but Super can handle both seamlessly."

Download Nedap- case study.mp4

The digest that runs the company

I think surprisingly the digest is, I would say, my most used feature. We have so much content flowing into Super that the weekly digest really doesn't work because I set it to a daily one because there's just too much content in the weekly digest that it doesn't work anymore.

Now, every weekday morning, André receives a summary of the previous day's activity across all connected platforms. As André puts it: "It's the only newsletter I read."

The digest has become so integral to his workflow that he's considering creating multiple versions: one for Slack discussions, another for Slite documentation updates, and others for specific data sources. But the real magic happens when these digests spark discussions.

"When you ask Super a question later, it often references both the original documentation and subsequent discussions. It gives a very nicely well-rounded answer because it can see the full conversation around any topic."

Bespoke intelligence for every team

Nedap's created a system of specialized assistants for all teams.

Take the customer success assistant.

Tightly integrated with HubSpot, it provides CSMs with instant access to customer histories, previous issues, and context from past interactions. When a client calls with a complex question, the team can quickly surface relevant information without interrupting colleagues or scheduling unnecessary meetings.

"Customer success people can get overviews of who contacted them, what issues were happening with that customer, what explanations have been provided."

There's also the on-call assistant.

With multiple teams rotating through on-call responsibilities, not everyone can master every system. The assistant draws from incident histories, post-mortems, and troubleshooting documentation to help developers handle issues outside their core expertise.

"Even if it's not in your core competency, it's a great starting point."

Rather than escalating immediately or spending precious minutes searching through scattered documentation, on-call engineers can get contextual guidance based on similar past incidents.

Download Nedap- case study 2.mp4

What André wants - Super everywhere

André's vision extends well beyond today's question-and-answer interactions. He's thinking about active intelligence systems that participate naturally in work:

"I want to have a meeting agent that you can actually ask a question during discussions, or that can proactively give information based on the conversation being had, like a human but with our entire knowledge base available."

Institutional memory that never forgets, never sleeps, and joins every conversation when needed.

His team continues exploring browser extensions, API integrations, and those active meeting participants he envisions.

For now, though, Nedap has found something many growing companies struggle to achieve: knowledge sharing that actually gets better as the organization scales. The daily digests keep evolving, specialized assistants learn from real conversations, and teams discover new applications organically.