From Sensitive Data to Smarter Workflows: How a Research Center Adopted a Closed, Self-Hosted Chatbot System

The Starting Point

In one of Europe’s most respected research centers, the team was facing a dilemma: how to embrace the power of AI without exposing their sensitive, confidential data to external risks. Researchers were spending countless hours on repetitive tasks like documentation, experiment note searches, and internal knowledge sharing. AI could clearly accelerate their work — but data privacy was non-negotiable.

The Challenge

Off-the-shelf chatbot solutions weren’t an option. Cloud-based services raised red flags around confidentiality, regulatory compliance, and intellectual property protection. At the same time, researchers needed a system that was both reliable and scalable — something that could serve over 100 staff members simultaneously without lag or disruption. The question was: how do you unlock AI productivity without opening the door to data leaks?

The Turning Point

That’s where we stepped in. Together with the center’s IT team, we designed and deployed a self-hosted LLM system tailored for their specific needs. Instead of relying on public APIs, we set up a multi-instance deployment of the latest LLaMA model, carefully optimized to run on the center’s own hardware.

We didn’t just drop in the model — we engineered the full ecosystem:

• Hardware infrastructure capable of handling high-volume, real-time requests.
• Secure installation and configuration to ensure the system stayed fully isolated from external networks.
• Monitoring and support to guarantee uptime and performance.
• Quality control workflows that test every new LLM version before updating, so researchers always work with a validated and reliable system.

The Outcome

The result was transformative. More than 100 researchers now have instant access to an AI assistant that can answer queries, draft reports, and surface past research with ease — all without sensitive data ever leaving their secure environment. Productivity across teams improved significantly, with routine tasks accelerated and collaborative workflows streamlined.

Beyond performance gains, the project gave the leadership peace of mind: their intellectual property stays in their hands, protected by a closed AI ecosystem built for privacy first.

Looking Ahead

This closed chatbot system has become the foundation for broader AI adoption inside the research center. With a scalable, future-proof setup, they’re already exploring domain-specific fine-tuning and AI-driven knowledge discovery. And with the flexibility to expand into private cloud, on-premise servers, or even enterprise-protected APIs, they now have options for the future that don’t compromise on control.

Let’s Explore What’s Possible

If your organization faces the same tension between AI innovation and data security, you don’t have to choose one over the other. We help research labs, enterprises, and institutions build self-hosted, privacy-first AI systems that scale with their needs.

If you see your story in theirs, let’s explore what’s possible together.