Case 01 · Open courtyard
Predictive scoring applications
Operations teams need a number they can use, not a dashboard they admire. We frame the decision, train against data that actually arrives, and place the score inside the existing cycle.
Typical contents: feature store, evaluation report, application API, override path.
Case 02 · Terracotta room
Computer vision pipelines
Image in, structured result out. The model, the capture path and the review screen stay distinct so a miss is visible and a retraining cycle has a place to start.
Case 03 · Cobalt wall
AI mobile applications
Field software that captures, infers and reports. The model travels with the product; the human remains able to disagree.
Case 04 · Pool terrace
Custom machine learning integration
When a model already exists, we give it software: authentication, versioning, monitoring and a release path that a product team can own.
Case 05 · Warm stone
Intelligent product software
Applications where machine learning is one room among others: accounts, audit, notifications, handover. We keep those rooms connected without letting the model occupy the whole plan.
Talk about a similar briefNo invented clients. These are the shapes of work we take on as a machine learning technology company in London.