We design and train machine-learning models for companies that have real data problems. No off-the-shelf demos. Every system we ship runs on your infrastructure and answers questions your team actually asks.
Send us your problem
Four practice areas. Each one starts with your data, not a sales pitch.
We build regression and classification models that forecast demand, flag anomalies and score leads. Training happens on your historical records, typically six to twelve weeks of labelled data. Outputs feed directly into your existing dashboards or ERP through a REST endpoint.
Invoices, contracts, regulatory filings: our OCR and NLP pipeline extracts structured fields from scanned or digital documents with over 96% field-level accuracy. The system learns your document layouts after roughly 200 annotated samples, then runs unattended.
Custom chatbots and voice assistants grounded in your knowledge base. We fine-tune large language models on your internal documentation so the bot answers with facts from your domain, not generic internet text. Response latency sits under 800ms for most queries.
Quality inspection on production lines, shelf monitoring in retail, safety compliance on construction sites. We train object-detection and segmentation models on images captured by your existing cameras. Typical turnaround from first image batch to production-ready model: five weeks.
Two examples that show how the numbers moved after deployment.
A 140-vehicle fleet was over-allocating drivers on Tuesdays and running short on Fridays. We trained a gradient-boosted model on three years of dispatch records, weather data and local event calendars. The model now predicts next-day parcel volume within 4.2% error.
Outcome: 18% reduction in idle driver hours over six months.
Accounts payable staff spent roughly 22 hours per week keying data from subcontractor invoices into their ERP. Our document-intelligence pipeline now extracts supplier name, line items, VAT and totals automatically. A human reviewer checks flagged exceptions only.
Outcome: processing time dropped to under 5 hours per week.
Five stages, usually eight to fourteen weeks end to end.
We review your data sources, define success metrics and agree on a fixed-price quote within one week.
Our engineers profile your datasets for quality gaps, bias risks and labelling needs. You get a written report.
Iterative experiments tracked in MLflow. You see accuracy curves and confusion matrices after each sprint.
We containerise the model and deploy it to your cloud or on-premise servers with monitoring dashboards.
Twelve months of retraining, drift detection and priority bug fixes included in every contract.
It depends on the task. For tabular prediction models, a few thousand rows of clean historical records is often enough to get a useful baseline. Image classification tasks generally need at least 500 labelled images per category. During the scoping call we assess what you have and tell you honestly if it is sufficient.
Yes. Most of our client meetings happen over video. Our office is in Carroll-on-Jakubowski, but we have active projects with firms in Bristol, Manchester and two in mainland Europe. On-site visits are possible across the UK when the project warrants it.
Small proof-of-concept engagements start around £8,000. A full production deployment with integration, testing and twelve months of support typically falls between £25,000 and £70,000. We quote fixed prices after the scoping call so there are no surprises.
You do. Model weights, training scripts and evaluation notebooks are handed over at the end of every project. We retain no copies of your data after the contract concludes unless you ask us to for ongoing retraining.
We deploy on AWS, Azure and GCP regularly. If you run on-premise servers or a private cloud, that works too. Our containers are platform-agnostic and we write Terraform or Ansible scripts for reproducible infrastructure setup.
Describe the problem you want to solve. We will reply within one working day with initial thoughts on feasibility and a rough timeline.
4 Fred End, Carroll-on-Jakubowski, Wales, TM2 8XU, United Kingdom