We're a young studio, and we won't pretend otherwise. These are the projects we can show, written up honestly, including one that did not work. As client projects close, and clients agree to be named, they appear here as case studies with verified numbers. How we build is documented separately, on work notes.
Quince AI is incredibly professional and responsive to both stated and unstated needs, presenting solutions that have the potential to make a big difference in both resource efficiency and behavior.
Method and regulation notes now live on their own page: read the work notes →
A circular economy project with Wargön Innovation, funded by Vinnova: image recognition and near infrared spectroscopy fused into an automated sorting process that sorts toward real buyer demand.
How we built an AI talent matching platform for consulting firms and recruiters, now in production at Itmotive and Braha IT. What we built, what we ruled out, and where we stopped the AI.
One traceable workspace for compliance assessment across NIS2, the EU AI Act, ISO 27001 and DPIA. Where the AI sits, where it deliberately does not, and what is still being built.
We launched an app that valued used clothes from a photo and matched them to local buyers. Then a regulation reshaped the market. What the technology proved, and what we misread.
A project earns a place on this page only when it can carry a name and a number. Every case study we publish follows the same four-part structure, and until a project can be told that way, it stays a work note.
The fastest route to a case study is a project that works. Start with a two-week ML Feasibility Sprint (fixed scope, från 95 000 kr), and we'll earn the right to write it up.