We build and deploy machine-learning models, natural-language processors and computer-vision systems that solve specific problems you face today. No hype, no vaporware: just measurable results delivered within weeks.
Most AI consultancies talk in abstractions. We prefer specifics. Here are the four areas where we spend our days, and where our clients see returns.
We train regression and classification models on your historical data to forecast demand, churn and revenue. A typical engagement starts with a two-week data audit, followed by model development and deployment into your existing dashboards.
From defect detection on production lines to automated document scanning, our convolutional-network pipelines process images at scale. We have deployed inspection systems that reduced manual quality checks by 73% for a West Yorkshire manufacturer.
Chatbots, sentiment analysis, contract extraction: we fine-tune large language models on your domain vocabulary so they understand the terminology your staff and customers actually use, not just generic English.
Not every problem needs a neural network. We spend a paid discovery day with your team, map the processes where AI will save the most time or money, and hand you a prioritised roadmap with realistic cost estimates.
These figures come from engagements completed between January 2022 and March 2025.
We follow a four-step process. Each step has a defined deliverable, so you know exactly what you are paying for before the next phase begins.
A one-day on-site or remote workshop where we interview stakeholders, inspect data sources and identify the three highest-value AI opportunities. You receive a written brief within five working days.
We build a working prototype on a representative subset of your data. This phase lasts two to four weeks and ends with a live demo you can test against real scenarios.
The validated model is packaged into a containerised service, integrated with your APIs or data warehouse, and stress-tested. Typical timeline: four to eight weeks depending on complexity.
Models drift. We set up automated performance alerts and retrain on fresh data monthly or quarterly. You get a dashboard showing accuracy, latency and usage metrics in real time.
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