Retail and e-commerce
Demand forecasting, personalised product recommendations, dynamic pricing models. A fashion retailer reduced overstock write-offs by 22% in the first quarter after deploying our demand model.
Service catalogue
Predictive analytics
We build models that forecast future outcomes from your historical data. Common applications include demand forecasting for supply chains, customer churn prediction for subscription businesses and credit risk scoring for lenders.
What you get: a trained model deployed as an API or batch pipeline, a monitoring dashboard, a technical handover document and a plain-language report explaining model accuracy, key features and known limitations. Typical timeline is six to ten weeks depending on data complexity.
We use gradient-boosted trees (XGBoost, LightGBM) for tabular data and recurrent or transformer-based architectures for time-series problems. The choice depends on your data volume and latency requirements. For a mid-size retailer with 200,000 SKUs, we recently achieved a mean absolute percentage error of 8.3% on 12-week demand forecasts, down from 19% using their previous rules-based approach.
Computer vision
If your problem involves images or video, this is the service for you. We train convolutional neural networks and vision transformers to detect objects, classify images, segment regions of interest or read text from documents.
Real examples from our project history: a food manufacturer uses our defect-detection model to inspect packaging on a production line running at 120 units per minute. A property management company uses our model to classify building damage from survey photos, routing urgent repairs to the right contractor within minutes instead of hours.
Deliverables include the trained model, an inference pipeline (cloud or edge device), labelling guidelines for future data, and a retraining script. We can also build a simple web interface for manual review of low-confidence predictions.
Natural language processing
We fine-tune large language models on your domain data to power chatbots, extract information from contracts, summarise long documents or classify support tickets by urgency and topic.
A legal-tech client asked us to extract key clauses from commercial leases. Our extraction model processes a 40-page lease in under 10 seconds and identifies rent review dates, break clauses and service charge caps with 94% precision. Their paralegals previously spent 45 minutes per document doing the same task manually.
NLP projects include the fine-tuned model, an API endpoint, evaluation metrics on your test set, and a guide for updating the model when your terminology or document formats change. We handle data privacy carefully: if your documents contain personal data, we can train on-premise so nothing leaves your network.
Process automation
Not every AI project needs a complex model. Sometimes the biggest gains come from automating repetitive data tasks: pulling numbers from PDFs, reconciling records across systems, generating weekly reports from raw data or routing incoming emails to the right department.
We build Python-based automation pipelines that run on a schedule or trigger from an event (a new file arriving in a folder, a webhook from your CRM). Where a task requires judgement we add a lightweight classification model; where it does not, we use rule-based logic and keep things simple.
One accounting firm we work with automated their monthly VAT reconciliation. The pipeline pulls transaction data from three sources, matches records by reference number and amount, flags discrepancies and produces a formatted Excel report. A task that took two staff members a full day now runs in 12 minutes overnight.
AI strategy consulting
If you are not sure where to start, this service gives you a roadmap. We spend two to four weeks interviewing your teams, reviewing your data landscape and identifying the three to five highest-value opportunities for AI in your organisation.
The output is a prioritised roadmap document. Each opportunity is scored on expected business impact, data readiness, technical complexity and estimated cost. We include a recommended sequence so you can start with a quick win and build internal confidence before tackling harder problems.
Strategy engagements are priced as a fixed fee, typically between £6,000 and £14,000 depending on the number of departments and data sources involved. The roadmap is yours to execute with us, with another provider, or with your own team.
Indicative pricing
Every project is quoted individually after the discovery phase. The figures below give you a rough idea of where costs land for each tier of engagement.
Discovery only
From £4,500
- Two-week data and feasibility assessment
- Written report with accuracy estimates
- Fixed-price quote for the build phase
- No obligation to proceed
Standard build
£18,000–£45,000
- Discovery, data prep, model build and integration
- Deployed API or batch pipeline
- Monitoring dashboard
- Technical handover and documentation
- 30 days of post-launch support
Enterprise build
£45,000–£75,000+
- Complex multi-model systems
- On-premise or hybrid-cloud deployment
- Custom UI for end users
- Staff training workshops
- Quarterly retraining retainer available
Industries we have worked in
Our team has delivered projects across several sectors. Here is a snapshot of the kind of work we have done in each.
Healthcare
Referral triage, patient no-show prediction, clinical document summarisation. We work within NHS data governance frameworks and can deploy models inside N3/HSCN-connected environments.
Financial services
Credit scoring, fraud detection, regulatory document extraction. Our models are built with explainability in mind so they satisfy FCA expectations around automated decision-making.
Manufacturing
Visual quality inspection, predictive maintenance for production equipment, yield optimisation. One client reduced unplanned downtime by 35% after we deployed a vibration-analysis model on their CNC machines.
Ready to discuss your project? Call us on +44 333 082 1573 or send a message.