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Service 05 — Models

Machine Learning

Custom models for prediction, classification and automation — trained on your data, tuned to your domain, and built to earn their keep. When off-the-shelf AI can't see what matters in your business, a model built on your own data can.

What it is

Models trained on your data — not someone else's average

Generic AI is trained on the whole internet; your business is specific. Machine learning is how you capture what's specific — the patterns in your customers, your operations, your history — in a model that predicts, classifies or automates with an accuracy a generic tool can't match.

We focus on models that actually ship and pay back: scoped to a real decision, measured against a real baseline, and deployed where they make a difference.

What's included

The right model for the job

01

Predictive models

Forecast demand, churn, risk or revenue from your own historical data.

02

Classification & scoring

Automatically sort, tag, prioritise or score records, leads and documents.

03

Recommendation systems

Surface the right product, content or next action for each individual user.

04

Automation models

Take repetitive, judgement-based tasks off your team's plate, reliably.

05

Model evaluation

Honest accuracy, bias and baseline testing so you know what you're really getting.

06

Deployment & monitoring

Models put into production and watched for drift — not left to gather dust in a notebook.

How it works

From business question to working model

Step 1

Frame

We turn a business question into a measurable modelling problem.

Step 2

Prepare

We assemble and clean the data the model will learn from.

Step 3

Train & test

We build, tune and honestly evaluate the model against a baseline.

Step 4

Deploy

We ship it into your workflow and monitor it over time.

What you walk away with

A model you can actually rely on

FAQ

Questions, answered

How much data do we need?

Often less than people fear. We'll tell you early whether your data is enough for the problem — and if not, exactly what would close the gap.

How do we know the model is actually good?

We measure it against a clear baseline and report accuracy, errors and bias honestly. If it doesn't beat the baseline, we tell you rather than ship it.

Is this different from generative AI / LLMs?

Yes. Machine learning here means models trained on your data for prediction and classification; for language and content we also offer LLM optimisation.

Can the model run in our systems?

Yes — we deploy models into your stack and monitor them, so they keep performing as your data and business change.

What about bias and fairness?

We test for it explicitly and, where relevant, design the model and process to keep decisions fair, explainable and defensible.

Got a prediction or decision worth automating?

Tell us the question; we'll tell you honestly whether a model can answer it — in a free consultation.

Book a free consultation →