We bridge the gap between what AI can do and what institutions actually use. We turn cutting-edge capability into operational systems organizations can own and sustain.
We work with teams in climate, democracy, healthcare, and education.
Most AI is built to maximize convenience, automation, and ultimately dependency.
The institutions solving society's hardest problems need advanced AI capability. But they can't accept black-box systems from vendors they can't leave. They need technology they can understand, modify, and take responsibility for.
The market doesn't serve them. Consultancies optimize for billable hours. AI vendors optimize for lock-in. Startups optimize for scale. And the gap between what AI can do and what these institutions actually use keeps growing.
STL exists to close that gap, on terms that keep institutions in control.
We write about why institutional AI fails and what it takes to make it work.
We design and build AI-powered systems for complex data problems: pipelines, models, infrastructure, and applications. We start from your context, not from a template.
STL treats AI as infrastructure inside complex social systems.
We stay through the hardest part: when technology meets real workflows and real people. Every engagement ends with you more capable than when we started.
A successful project is an organization that can continue without us.
Workshops, trainings, and keynotes for teams and leadership navigating AI adoption. We help you understand both the potential and the limits of what technology can do.
The best technology decisions come from leaders asking better questions.
We reinvest profits into 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.
Impact funded by profit, not charity.
Learn more about what we do
How we work, what we deliver, and on what terms


The course Social Technology Lab put together for us was one of the
most thorough, in-depth, and inspiring moments of knowledge transfer I have experienced . The others and I left the room after eight hours with more energy than when we walked in, our heads full of relevant concepts and artifacts we can use for applying IAMA and creating our AI Governance plan. Chapeau!
Five principles that define how we work:
Independence over growth
Sovereignty over convenience
Responsibility over neutrality
Context over templates
Impact funded by profit, not charity
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