Machine learning development services.
Predictions your business can act on.
Custom ML models for forecasting, scoring, recommendation and detection, deployed and monitored.
The problems we solve first.
Data quality
Models are only as good as the data behind them.
Explainability
Business teams need to understand predictions.
Drift
Models degrade as the world changes.
What you get.
Every engagement includes design, engineering, evaluation, security review and handover from one senior team.
Feature engineering
Signals built from your data.
Model training
Forecasting, classification and ranking.
Explainability
Reasons behind each prediction.
MLOps
Pipelines, versioning and deployment.
Monitoring
Accuracy and drift alerts.
A/B testing
Measured business impact.
Machine learning development, by industry.
How we ship AI that holds up.
Evaluation comes before scale. You see it working on your data before you commit to the full build.
Discover
Pick the task, define what “good” means and collect sample data.
Prototype
A working version on your real data, shown to real users.
Evaluate
Automated tests for accuracy, latency, cost and safety.
Productionise
Security, scaling, integrations and admin controls.
Monitor
Quality, drift and spend tracked; prompts and models improved.
Three ways to start.
AI sprint
One use case, prototyped on your data and tested with users.
You leave with · Prototype + go/no-goPilot
A production-grade version for one team, with evals and monitoring.
You leave with · Live pilot + ROI dataAI team
A dedicated squad that ships and improves AI across your products.
You leave with · Roadmap deliveredQuestions, answered.
Most clients start with a two-week AI sprint. Pilots and production builds are priced after the sprint, once we know what works on your data.
Ready to try machine learning development? Start with a sprint.
Tell us the task. An AI architect replies within one business day with a sprint plan. NDA on request.