Data Science
Machine learning and analytics that answer real business questions — forecasting, scoring, optimization — built on your data and deployed where decisions happen.
From raw data to running models
Frame the question
We turn a business question into a modelling problem with a measurable target and a baseline to beat.
Explore & model
Rapid iterations on your data; you see honest interim results, including when the data cannot support the goal.
Validate
Models tested against holdouts and business logic — accuracy claims you can defend.
Deploy & monitor
Models shipped into your stack with drift monitoring, so performance is watched, not assumed.
Every engagement ends with
Why it pays off
Decisions, not dashboards
Models embedded where choices get made — pricing, planning, risk — not another report.
Honest feasibility
We tell you early if the data cannot answer the question. That candor saves quarters.
Performance that lasts
Monitoring and retraining keep models useful after month three.
When you need this
You collect plenty of data but decisions are still made on gut feel.
A forecasting, scoring or optimization problem has clear money attached.
A previous data science effort produced notebooks, not production value.
How we work together
Feasibility sprint
Data audit and baseline model, 2–3 weeks, fixed price.
Model to production
Full build, deployment and a monitoring retainer.
Typical timeline Feasibility in 2–3 weeks; production models typically 6–10 weeks.
Common questions
How much data do we need?
Less than you fear, more than a spreadsheet. The feasibility sprint answers this precisely for your question.
Our data is messy — is that a problem?
It is normal. Cleaning and structuring is part of the sprint, and we tell you if quality genuinely blocks the goal.
Who maintains the models afterwards?
Your team, with our runbook and training — or we do, under the monitoring retainer.
Have a question your data should answer?
Tell us the decision you want to improve. Replies within 24 hours.
Get a tailored proposal →