Machine learning
services
MachineMachine learning that solves a real business problem, not a science project.
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Why machine learning projects stall without the right consultancy
Most businesses have the data and the ideas; the hard part is turning them into models people actually use.
48%
Models stuck at the pilot stage
A promising prototype is not the same as a model running in daily operations. Gartner’s 2024 AI survey found only 48% of AI projects reach production, taking eight months on average to get there.
Gartner, AI adoption survey, 2024. Click Here
49%
We can't prove it will pay back
Without a measurable outcome agreed up front, funding tends to stall. In the same Gartner survey, 49% named difficulty estimating and demonstrating the value of AI projects as the main barrier to adoption.
Gartner, AI adoption survey, 2024. Click Here
60%
No AI skills in house
Machine learning needs people who understand both the model and the business question. The UK Government’s AI Adoption Research found limited AI skills, expertise and knowledge cited as a barrier by 60% of businesses asked.
UK Government (DSIT), AI Adoption Research, 2026. Click Here
The answer is rarely a bigger model; it is a clear business measure agreed before anyone builds.
Introduction
Practical models built around one measurable outcome
Machine learning uses your existing data to predict outcomes, such as demand, risk or likely customer behaviour, rather than simply reporting on what already happened. Cybit builds and deploys models against one clearly defined business question at a time, using the data platform you already have. Businesses need this when they are ready to move from hindsight to foresight in a specific, measurable part of their operation.
Our Delivery Framework
Why Choose Cybit
We start every machine learning engagement with the business question, not the algorithm, because that is where most projects go wrong. Our work with Microsoft Azure, Claude, Qlik Predict and OpenAI enhanced analytics for clients such as The Rudd Group shows how a well scoped model changes day to day decisions, not just a slide deck. Bring us the problem and we will tell you honestly if machine learning is the right answer.
Our Process
Assess
Understand where you are today, identify opportunities for improvement and build a clear picture of your technology landscape
Advise
Turn insight into action with expert guidance and recommendations based on your business goals
Deliver
Implement solutions that create measurable impact and lasting value
Support
Our proactive management, ongoing optimisation and expert support keeps your tech performing at its best
What's Included
Use case definition workshop, starting with the business question
Data readiness check against the chosen use case
Feature engineering and model development
Model validation and accuracy benchmarking
Deployment into your existing data platform
Monitoring for model drift and ongoing accuracy
Data
What the Analysts Say
IDC research commissioned by Microsoft puts the average return at $3.70 for every $1 invested in generative AI, with the highest performing organisations reporting considerably more. The variance is the point: return follows scope, not ambition.
IDC, The Business Opportunity of AI, commissioned by Microsoft, November 2024. Click Here
Helpful Information
Frequently Asked Questions
Machine learning uses existing data to predict outcomes such as demand, risk, maintenance need or likely customer behaviour, rather than reporting on what already happened.
Less than most people expect, but it has to be the right data. Quality and history matter more than volume. The readiness check tells you honestly whether the use case is viable before any model is built.
We say so. Some problems are better solved with a rule, a report or a process change, and a model built where none was needed becomes an expensive thing to maintain.
No. Cybit builds, deploys and monitors the model, and hands over documentation so your team understands what it does and when it needs attention.
Usually because the pilot proved the model could work but not that it was worth running. Gartner found only 48% of AI projects make it into production, and 49% of organisations struggle to estimate and demonstrate the value of AI. Agreeing the business measure before building is what closes that gap.
Solutions
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Roadmap Advisory & Strategy
Create a practical data and AI roadmap aligned to measurable business goals, investment priorities and risk.
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Let's Make Technology
Work for You
Whether you're scaling up, securing your data, or transforming your digital workspace – Cybit is your partner for strategic IT solutions.
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