We build AI systems that fit the way you already work: forecasting demand, reading documents automatically, spotting anomalies before they cost you money. No hype, just measurable gains.
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Why this matters
Staff spend hours each week copying figures between spreadsheets, manually reviewing invoices, or sifting through customer emails to find the urgent ones. These tasks are repetitive, error-prone, and they pull your best people away from work that actually grows revenue.
Worse, the data those tasks generate sits in silos. Sales figures in one system, stock levels in another, customer feedback in a third. Nobody has the full picture at once.
A well-designed AI pipeline connects those silos, reads incoming documents in seconds, and surfaces the patterns that humans miss. One logistics client reduced order-processing time by 63% within the first quarter. A retail chain used our demand forecasting model to cut overstock waste by 28%.
These are not theoretical improvements. They show up on the balance sheet.
What we deliver
Every engagement starts with your specific problem, not a pre-packaged product. Here are the areas where we have the deepest experience.
We train models on your historical data to forecast sales volumes, churn risk, equipment failure windows, and seasonal demand shifts. Output feeds directly into your existing dashboards or ERP.
Invoices, contracts, medical records, compliance forms: our NLP pipelines extract structured data from unstructured files. Average accuracy sits above 96% after the initial training phase, which typically takes two to three weeks.
Quality inspection on production lines, vehicle damage assessment for insurers, shelf-stock monitoring for retail. We design and deploy vision models that run on-premise or in the cloud, depending on latency requirements.
Customer-facing chatbots that actually resolve queries instead of looping through menus. Internal assistants that help your team search policy documents, technical manuals, or past project notes in natural language.
Not sure where to start? We run a structured discovery workshop, audit your data estate, and produce a prioritised roadmap. The output is a concrete plan with cost estimates, not a slide deck full of buzzwords.
Models decay as the world changes. We set up monitoring, retraining pipelines, and alert systems so your AI stays accurate over time. Typical SLA includes monthly performance reviews and quarterly model refreshes.
How we work
A 45-minute conversation where we learn about your operations, data sources, and the specific outcome you want. No preparation needed on your side.
We examine your data quality, build a small-scale prototype, and share measurable results within two to four weeks. You see real numbers before committing further.
The approved model gets hardened, tested against edge cases, and connected to your live systems. We handle API design, security review, and user training.
Post-launch monitoring, performance dashboards, and scheduled retraining keep the system reliable. You get a dedicated point of contact, not a ticket queue.
Common questions
It depends on the task. A demand-forecasting model might need 18 months of sales history. A document-extraction system can start with as few as 200 annotated samples. During the discovery call we assess what you have and whether it is sufficient, or whether we need to augment it.
A proof of concept usually runs between £8,000 and £20,000 depending on complexity. Full production builds range from £25,000 to £120,000. We provide a fixed-price quote after the data audit so there are no surprises.
Yes. About a third of our clients are based in Ireland, mainland Europe, or North America. We run projects remotely and visit on-site when the engagement requires it.
In our experience, no. The goal is to remove dull, repetitive tasks so your team can focus on decisions that require judgement, creativity, and customer empathy. Most clients reassign freed-up hours rather than reduce headcount.
The proof-of-concept phase delivers measurable output within two to four weeks. A full production deployment, including integration and testing, typically takes eight to fourteen weeks from kick-off.
All our support plans include automated drift detection. When accuracy drops below a threshold we agree on together, a retraining cycle triggers automatically. You receive a report explaining what changed and what was done about it.
Get in touch
Phone: +44 842 993 5642
Email: [email protected]
Address: 241 Rene Fields, Little Anderson, AP04 8RF, Northern Ireland, United Kingdom
Monday to Friday, 09:00 – 17:30 GMT
We aim to respond to every enquiry within one working day.