What We Do

We don't sell AI products. We don't run generic implementations. We work with organizations to understand their problem, build the right technology, stay through adoption, and leave them in control.

Everything we do follows one logic: the institution we serve should be stronger after we leave than when we arrived.

Build AI Infrastructure

We design and build AI-powered systems for complex data problems: pipelines, models, infrastructure, and applications. We start by understanding the problem, then specialize in situations where off-the-shelf solutions don't fit, where context, nuance, and domain expertise matter.

Most AI companies treat AI as a product, a model, or a consulting deliverable. STL treats AI as infrastructure inside complex social systems.

What this looks like in practice:

  • Data infrastructure and pipeline design
  • Custom AI/ML model development
  • System architecture for complex institutional environments
  • Integration with existing workflows and tools

Transfer Capability

We don't deliver and disappear. We stay through the hardest part, when technology meets real workflows and real people. Every engagement is designed to end with the client more capable than when we started. We document thoroughly and build for handover, not for ongoing dependency.

A successful project is not a shipped system. A successful project is an organization that can continue without us.

What this looks like in practice:

  • Co-building with internal teams from day one
  • Thorough documentation and knowledge transfer
  • Post-delivery support with a clear end date
  • Internal capability assessments and roadmaps

Training and Advice

We run workshops, trainings, and strategic advisory for leadership teams navigating AI adoption and IT migration. We help organizations understand both the potential and the limits of what technology can do.

The best technology decisions don't come from better vendors. They come from leaders asking better questions.

What this looks like in practice:

  • AI literacy workshops for leadership and teams
  • Strategic advisory on AI adoption and data strategy
  • Technical assessments: what's feasible, what's not, what's premature
  • Guidance on vendor selection, build-vs-buy decisions, and technology governance

Develop Public Tools

We reinvest profits into building open-source tools and frameworks that serve the public interest. What we build for clients becomes shared infrastructure. Wegeneralized from real use, not designed in the abstract.

What this looks like in practice:

  • Open-source tools and frameworks born from client work
  • Reusable components for common institutional AI challenges
  • Public documentation and guides

How We Work

Every engagement is different, but our approach follows a consistent logic:

1

Understand

We start with the human context. Wethe organization, the people, the problem. Before writing a single line of code, we invest in understanding what needs to be built and why.

2

Frame

We define the problem together. What are we actually solving? What does success look like? What's the simplest path to real value? This is where most of the hard work happens.

3

Build

We design and build. Weiteratively, close to real-world use. No big reveals after months of silence. We build with your team, not behind closed doors.

4

Adopt

We stay through adoption. The moment technology meets real workflows and real people is where most projects fail. We don't leave before that part is done.

5

Hand over

We build for your independence. Documentation, training, internal capability. Weeverything needed for you to continue without us. The engagement has a clear end.

Not sure what you need?

That's fine. Most organizations we work with start with a conversation, not a brief. Tell us what you're working on and we'll figure out together whether and how we can help.

Contact

Wil je meer weten over onze diensten of heb je een vraag? Wij zijn altijd bereikbaar voor een vrijblijvend gesprek of advies! Stuur een berichtje:

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