Machine Learning That Proves Itself in Six Weeks

A proof of concept on your data lands in 4–6 weeks with honest accuracy numbers — typically £5k–£15k. If the data can’t support the goal, you find out cheaply, not after a year.

Beyond Algorithms.
Building the neural pathways of your business.

Data science projects often fail not because of the math, but because of the engineering. A brilliant model trapped in a notebook delivers zero value. Without robust pipelines, scalability, and integration into live workflows, AI initiatives become expensive experiments rather than drivers of ROI.

A model in production is a strategic asset. We bridge the gap between theoretical data science and robust software engineering. Our machine learning services cover the entire lifecycle—from feature engineering to MLOps—ensuring your systems are transparent, explainable, and rigorously tested for reliability and growth.

Predictive power,
integrated at scale.

We deliver end-to-end machine learning solutions that solve specific business challenges with mathematical precision and engineering rigour.

Custom Predictive Modelling

We build tailored algorithms that forecast trends, demand, and behaviour with high accuracy, enabling proactive decision-making rather than reactive adjustment.

Intelligent Recommender Systems

Drive engagement and revenue with personalised discovery engines that understand user intent, context, and preference in real-time.

Anomaly & Fraud Detection

Protect your ecosystem with self-learning security models that identify irregularities, threats, and fraudulent patterns faster than human analysts ever could.

Natural Language Processing (NLP)

Unlock the value of unstructured text and voice data. We build systems that understand, interpret, and generate human language for support, analysis, and automation.

End-to-End MLOps & Deployment

We don't just train models; we operationalise them. Our MLOps pipelines automate deployment, monitoring, and continuous retraining for sustained performance.

What a typical engagement looks like

Typical budget£5k–£15k PoC
TimelineAccuracy numbers in 4–6 weeks
CadenceA working demo or report every two weeks — you watch it grow.
OwnershipSource code, files and IP handed over in full. No lock-in.
First stepA free estimate or a free 30-minute call — fixed, staged quote before any work starts.

Proof, not promises

Case study

PropMarker — property sourcing platform

Automated property analysis in production for UK investors.

View case study

500+ projects delivered since 2005  ·  4.5★ on Google  ·  Crown Commercial Service supplier

Frequently asked questions

How much does machine learning development cost?
A proof of concept typically runs £5k–£15k; production systems with pipelines, monitoring and retraining are quoted after the PoC proves value.
How long does a machine learning project take?
A PoC lands in 4–6 weeks with real accuracy numbers on your data. Production hardening typically adds 2–3 months, shipped incrementally.
What if the model does not perform?
You will know in weeks, not months — the PoC is designed to prove or kill the idea cheaply. If the data cannot support the goal, we say so plainly and stop.
What does the process look like?
Data review, then a fixed-price proof of concept with success criteria agreed up front. Honest accuracy numbers in 4–6 weeks; production hardening only after the PoC earns it.
What do you need from us to start?
A sample of your data and an hour with whoever knows it best. We will tell you quickly if the data cannot support the goal — before you spend, not after.
Who owns the trained model?
You do — the model, the training pipeline and the documentation. Deployed in your cloud or ours, exportable either way.
Ready for What’s Next?

Let's Build What's Next — Together

Not sure this is the right move yet? A free 30-minute call will tell you — no deck, no obligation.

4.5★ on Google reviews  ·  500+ projects delivered  ·  Crown Commercial Service supplier

020 8363 4905  ·  info@designdirect.io  ·  UK & India