When is machine learning not the right answer?

When clear rules would do the job, or when the data is too thin to learn from. We will tell you if a simpler approach works better.

AI & Data

Machine learning

From demand forecasting to fraud scoring, we build machine learning models on your data and run them reliably in production.

What you can expect

Discovery in 2–4 weeks, then project

01What's included

Predictive models that forecast, score and recommend, in production.

01
Data assessment
We check whether your data can support the model you need.
02
Model development
Features, training and validation against a clear success metric.
03
MLOps & deployment
Models served through APIs or batch jobs, with versioning.
04
Monitoring & retraining
Alerts when accuracy drifts, and a process to retrain safely.

02Is it right for you?

Ideal for

Not sure it fits? Book a free 30-minute call and get an honest answer.

Typical stack

03How we deliver

01
Discover
Typically 1–3 weeks
We map your goals, users and constraints, then define what success looks like in numbers.
02
Design
Typically 2–4 weeks
Architecture and experience are designed together, so the product is beautiful and buildable.
03
Build
Two-week sprints
Senior engineers ship in short, demo-able sprints with automated testing from day one.
04
Launch
Typically 1–2 weeks
Hardened, monitored and documented: we go live with a rollout plan, not a leap of faith.
05
Grow
Ongoing
SEO, paid acquisition and product analytics compound the value of what we built together.

04Proof

Much of this work is under NDA.

Tell us about your project and we will share relevant examples and references on a call.

05FAQ

It depends on the problem. A quick data assessment tells you whether you have enough, and what to start collecting if you do not.