Predictive analytics
Demand forecasting, churn scoring, and lead prioritisation models trained on your own historical data. We use gradient-boosted trees or neural nets depending on volume and explainability requirements.
The gap between ambition and execution
Most organisations know AI could help. Few know where to start without burning budget on experiments that never reach production.
What we keep hearing
- Data sits in five different systems and nobody trusts the reports.
- A previous vendor built a prototype that never left the laptop.
- Manual data entry eats forty staff-hours a week.
- The board wants "AI" on the roadmap but there is no internal ML team.
What we actually do about it
- Audit your data estate in week one, flag gaps, propose a realistic pipeline.
- Ship a minimum viable model to staging within six weeks.
- Automate extraction from invoices, contracts, or forms using fine-tuned NLP.
- Train your team to monitor, retrain, and extend the system after handover.
Services we deliver
Each engagement starts with a scoping workshop. We agree on success metrics before writing a single line of code.
Document intelligence
Extract structured fields from invoices, contracts, medical letters, or planning documents. Our pipelines handle PDFs, scanned images, and handwritten notes with accuracy above 94% on most corpora.
Process automation
We wire AI models into your existing ERP, CRM, or warehouse management system so decisions happen in real time. Think automatic reorder triggers, dynamic pricing adjustments, or smart ticket routing.
AI strategy and advisory
Half-day or two-day workshops for leadership teams who need a clear AI roadmap. We assess feasibility, estimate ROI, and rank use cases so you invest in the right problems first.
From first conversation to live model
Four phases, each with a clear deliverable. You approve before we move on.
1
Discovery workshop
We spend a morning with your team mapping data sources, pain points, and desired outcomes. By the end of the session you have a written brief with scope, timeline, and budget range.
2
Data audit and preparation
Our engineers connect to your databases, APIs, or file stores. We profile quality, handle missing values, and build a repeatable pipeline that refreshes automatically. This phase usually takes two to three weeks.
3
Model development and validation
We train candidate models, benchmark them against your KPIs, and present results in plain language. You see precision, recall, and real examples of correct and incorrect predictions before anything goes live.
4
Deployment and knowledge transfer
The final model runs inside your infrastructure or a managed cloud environment we set up for you. We document every component, train your analysts, and offer a 90-day support window included in the project fee.
A recent project in numbers
They reduced our mis-picks by 62% in the first quarter. The model flags anomalies before parcels leave the conveyor, which used to cost us roughly £11,000 a month in returns and re-shipments.— Operations director, West Midlands e-commerce fulfilment company (name withheld under NDA)
The engagement ran for ten weeks. We deployed a lightweight anomaly detection model on their existing camera feeds, connected it to the WMS via REST API, and handed over monitoring to their in-house data analyst.
Common questions
If yours is not here, call or email us directly.
Do we need a large dataset before you can help?
Not necessarily. Some techniques work well with a few hundred labelled examples. During the discovery workshop we assess volume and quality. If your data is too thin, we can recommend collection strategies or synthetic augmentation before committing to a full build.
How do you charge for projects?
Most engagements are fixed-fee, scoped after the discovery phase. Advisory workshops are priced per day. We do not bill hourly because it creates the wrong incentives for both sides.
Will the model run on our servers or yours?
Your choice. We can deploy to AWS, Azure, GCP, or on-premise hardware. If you have compliance constraints that require data to stay within the UK, we configure accordingly.
What happens after go-live?
Every project includes a 90-day support window. After that, we offer optional retainer agreements for model monitoring, retraining, and feature expansion. Many clients manage the system independently after the knowledge transfer sessions.
Can you work with our existing software vendors?
Yes. We regularly collaborate with ERP consultants, CRM integrators, and internal IT teams. We document our APIs and provide test environments so third parties can integrate without friction.
Speak with us
Tell us what you are trying to achieve. We will respond within one working day.
Visit or write
6 Becker Mount, Birmingham B1 1TF, West Midlands, United Kingdom
Call
+44 121 036 8077
Email
[email protected]
Office hours: Monday to Friday, 09:00 – 17:30 GMT