We build prediction models, automate repetitive workflows and audit existing AI systems for UK mid-market companies. No hype decks. No six-month "discovery phases." You get a working prototype within four weeks or we pause billing.
Talk to our AI team
Most AI consultancies sell strategy decks. We write production code. Here is where we spend our time.
We train supervised models on your historical data: demand forecasting for retailers, churn prediction for subscription businesses, fault detection for manufacturers. Each model ships with a monitoring dashboard so you can see accuracy drift before it becomes a problem. Typical training cycle runs two to three weeks using your last 18 months of records.
Invoices, contracts, insurance claims: if your staff spend hours copying fields from PDFs into spreadsheets, we replace that with an extraction pipeline. Our current best system handles 1,200 invoice pages per hour with 97.6% field-level accuracy on structured UK formats.
Already running a model you bought or built in-house? We test it for bias, measure real-world accuracy against the numbers your vendor quoted, and produce a plain-language report your board can read. We reference the EU AI Act risk categories even for UK-only deployments because most clients trade with Europe at some level.
Not every problem needs a neural network. Sometimes a well-designed rules engine, an API integration, or a lightweight classification model saves more time than a large language model. We pick the smallest tool that solves the job, which keeps your hosting costs low and your system easy to maintain.
Before any modelling begins, we spend three to five days examining your databases, spreadsheets and third-party feeds. The deliverable is a scored matrix: which data sources are ready, which need cleaning, and which gaps you should fill before an AI project makes financial sense. This assessment is priced separately and carries no obligation to continue.
Every engagement follows this sequence. Steps overlap where it makes sense, but the order stays fixed because skipping the data audit is how AI projects fail.
45-minute video call. We ask about your data, your bottleneck, and your budget ceiling. No NDAs needed at this stage.
Three to five working days. We connect to a read-only copy of your data and score its quality.
A working model or pipeline you can test with real inputs. Usually delivered inside four weeks.
We run the prototype against held-out data and measure accuracy, latency, and edge-case behaviour.
Production rollout on your infrastructure or a managed cloud instance. Includes 90 days of monitoring.
We can share these because each client gave written permission. Names are used with consent.
This 40-person legal firm processed roughly 900 supplier invoices per month by hand. Two staff members spent about 12 hours each week on data entry alone. We deployed a document extraction pipeline in March 2024. Within six weeks the manual entry time dropped to under two hours per week, and the error rate on VAT calculations fell from 4.1% to 0.3%. Annual saving: approximately £38,000 in labour reallocation.
Moorland produces craft soft drinks and sells through 120 independent retailers across central Scotland. Their previous forecasting relied on last year's sales plus a seasonal multiplier. We trained a gradient-boosted model on three years of order data, weather records, and local event calendars. Forecast accuracy improved from 62% to 88% at the weekly SKU level. Overproduction waste dropped by 31% in the first quarter after deployment.
Athena manages 2,400 residential lets. Void periods cost them an average of £1,100 per property. We built a classification model that flags tenants likely to leave within 90 days, using maintenance request frequency, payment timing patterns, and local rental market data. The model correctly identified 79% of departures in its first six months, giving the lettings team enough lead time to begin marketing before notice was formally given. Void days fell by 22%.
A data readiness assessment starts at £2,800. A full prototype-to-deployment engagement for a single use case usually falls between £15,000 and £45,000 depending on data complexity and integration requirements. We quote fixed prices after the scoping call, not day rates.
No. We can work on-premises if your compliance framework requires it. About 40% of our clients keep everything on their own servers. We bring our own hardware for the training phase if needed.
Most data is messy. That is why the audit phase exists. We will tell you exactly what needs fixing, how long the cleaning will take, and whether the project is still viable after accounting for that effort. Sometimes the honest answer is "not yet," and we would rather say that early than bill you for a model trained on unreliable inputs.
Yes, and we prefer it. Your team knows your infrastructure better than we ever will. We provide documented APIs, deployment scripts, and a handover session so your developers can maintain the system after we leave.
Retail, property management, legal, manufacturing, and food and drink are our strongest verticals. We have also completed projects in logistics and financial services. If your industry is not listed, the scoping call is free, so there is no risk in asking.
Send us a short description of what you are trying to solve. We reply within one working day, usually faster.