Predictive analytics
Demand forecasting, churn prediction, and inventory optimisation models trained on your transaction history. One retail client reduced overstock write-offs by 23% within the first quarter using our demand model.
The challenge
Most AI projects fail before they launch
Around 85% of machine-learning initiatives never reach production. The reasons are almost always the same: unclear goals, messy data, and models that work in a notebook but break in a live environment. We exist to close that gap.
What goes wrong
Teams buy expensive platforms before defining the question they need answered. Data sits in five different formats across three departments. A proof of concept impresses the board, then stalls because nobody planned how to integrate it with the order management system or the CRM.
Six months later the budget is spent, the vendor is gone, and the spreadsheet is back.
How we fix it
We start with your decision, not our technology. What choice does a human make ten times a day that could be faster or more accurate? We scope around that single question, connect to your existing data, build the smallest model that answers it reliably, then deploy it where your staff already work.
Only after that first win do we expand. Incremental value, every sprint.
Our process
Four stages from idea to running system
1
Audit and scope
We spend two days on-site (or on video) reviewing your workflows, data sources, and existing software. You receive a written assessment listing the three highest-value AI opportunities ranked by cost, complexity, and expected return.
2
Data preparation
Clean data is 80% of the work. Our engineers connect to your databases, warehouses, or flat files, standardise schemas, handle missing values, and build a reproducible pipeline so the model can retrain itself on fresh data every week without manual effort.
3
Model development
We train, validate, and stress-test candidate models against your own historical outcomes. You see accuracy metrics, error distributions, and edge-case behaviour before anything goes live. Typical turnaround: four to six weeks for a first deployable version.
4
Deployment and monitoring
The model runs inside your infrastructure or on a managed cloud instance we set up for you. Dashboards track prediction quality in real time. If accuracy drifts below the agreed threshold, automatic retraining kicks in and we get an alert.
What we deliver
Services built around measurable outcomes
Intelligent document processing
Invoices, contracts, and compliance forms extracted, classified, and routed automatically. Our pipeline handles scanned PDFs, handwritten notes, and mixed-language documents with field-level confidence scores your team can audit.
AI strategy consulting
Half-day and full-day workshops for leadership teams who want to understand where AI fits in their roadmap. We map your data maturity, identify quick wins, and produce a prioritised twelve-month plan with budget estimates.
Custom model training
When off-the-shelf tools fall short, we design architectures from scratch: computer vision classifiers for quality control lines, NLP models fine-tuned on your domain vocabulary, or reinforcement learning agents for logistics routing.
Common questions
Things clients ask before we start
How much data do we need before AI becomes viable?
It depends entirely on the task. A straightforward classification model can learn useful patterns from a few thousand labelled examples. Complex forecasting across many variables may need hundreds of thousands of rows spanning at least two full seasonal cycles. During our audit stage we measure what you have and tell you honestly whether it is enough or what gap-filling steps are needed.
Do you replace our existing software?
No. Our models plug into whatever you already use. We expose predictions through a REST API, a webhook, or a direct database write, whichever suits your stack. If you run SAP, Dynamics, or a custom ERP, we have done integrations with all three.
What does a typical engagement cost?
A scoping audit starts at £2,400. End-to-end model development projects range from £12,000 to £60,000 depending on data complexity, integration depth, and ongoing monitoring requirements. We quote fixed prices after the audit so there are no surprises.
Who owns the trained model?
You do. Every model, pipeline script, and documentation artefact we produce is yours to keep. We can continue to manage and retrain it under a support contract, but you are never locked in.
How do you handle sensitive or regulated data?
We work under a signed data processing agreement that complies with UK GDPR. For healthcare and financial clients we deploy models inside their own virtual private cloud so data never leaves their perimeter. Audit logs record every access event.
Get in touch
Tell us what you are trying to solve
We respond to every enquiry within one working day. If you prefer a phone call, ring us directly or leave your number in the message and we will call you back.
Address:
850 Oxford Road, Olson-under-Friesen, Scotland, LE24 8PF, United Kingdom
Phone:
01187 858936
Email:
[email protected]