AI & Automation
Machine Learning & MLOps
Forecasting, scoring and classification where a statistical model is the right tool rather than a language model. The deployment and monitoring matter more than the model.
In short
Models trained, deployed and monitored.
What we deliver
- Feature engineering against your real history
- Model selection judged on business cost, not accuracy alone
- Confidence intervals surfaced to whoever acts on the output
- Drift monitoring and a retraining path
A good fit when
- Demand, risk or churn is currently estimated by eye
- A notebook model exists and never reached production
- Predictions are made but nobody tracks whether they were right
Technologies and methods
Chosen for each project, to fit your systems and your team.
- Python
- XGBoost
- MLflow
How we deliver
From first conversation to production.
Four stages on every engagement, scaled to the size of the project.
- 1
Understand
Clarify the users, goals, constraints, and current systems.
- 2
Plan
Map the main components, data, and integrations before implementation.
- 3
Build
Develop and review the work in small, testable increments.
- 4
Prepare
Plan deployment, operations, documentation, and ownership.
More in AI & Automation
- AI EngineeringProduction AI systems, end to end.
- Agentic AI SystemsMulti-agent systems with approval gates.
- Generative AI & LLMsLanguage models wired into your systems.
- RAG & Enterprise SearchAnswers from your documents, with citations.
- AI Workflow AutomationManual work automated, every step audited.
- Intelligent Process AutomationRepetitive steps removed from daily work.
- Computer VisionImages and video turned into records.
- Document IntelligenceStructured data out of unstructured files.
- Conversational & Voice AIAssistants that cite sources and refuse.
- AI Strategy & GovernanceWhat to automate, and what to keep human.
- AI EnablementYour team productive with AI tooling.
Prefer to talk it through?
A private consultation, 30 minutes with the founder, in your time zone.
Interested in Machine Learning & MLOps?
Tell us what you are working on. We start by understanding the problem, the people, and the systems involved.