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.
We design and build AI-powered systems for complex data problems.
AI as infrastructure inside complex social systems.
We stay through adoption and build for handover, not dependency.
A successful project is an organization that can continue without us.
Workshops, trainings, and keynotes on AI adoption and literacy.
The best decisions come from leaders asking better questions.
Open-source tools and frameworks that serve the public interest.
Generalized from real use, not designed in the abstract.
Every engagement is different, but our approach follows a consistent logic:
We start with the human context. We study the organization, the people, the problem. Before writing a single line of code, we invest in understanding what needs to be built and why.
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.
We design and build. We build iteratively, close to real-world use. No big reveals after months of silence. We build with your team, not behind closed doors.
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.
We build for your independence. Documentation, training, internal capability. We deliver everything needed for you to continue without us. The engagement has a clear end.
We design and build AI-powered systems for complex data problems — pipelines, models, infrastructure, and applications — specializing in situations where off-the-shelf solutions don't fit, where context, nuance, and domain expertise matter. STL treats AI as infrastructure inside complex social systems.
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. A successful project is an organization that can continue without us.
We run workshops, trainings, and keynotes for teams and leadership navigating AI adoption. The best technology decisions don't come from better vendors. They come from leaders asking better questions.
We reinvest profits into building open-source tools and frameworks that serve the public interest. What we build for clients becomes shared infrastructure — generalized from real use, not designed in the abstract.
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