We design, train, and deploy AI systems for companies that need measurable output. If your model lives only in a notebook, we fix that. Based in Northern Ireland, working with clients across the UK and Europe.
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Every engagement starts with a question: what decision does your business need to make faster or more accurately? We work backwards from that answer.
We train classification, regression, and generative models on your data. Not a generic API wrapper. Your data stays on your infrastructure if that matters to you, and it usually does. Typical turnaround for a proof-of-concept is four to six weeks.
Document classification, entity extraction, sentiment scoring, and summarisation pipelines. We handle messy, real-world text: scanned PDFs, customer emails with typos, regulatory filings with nested sub-clauses. Our NLP stack runs on transformer architectures fine-tuned to your domain vocabulary.
Defect detection on manufacturing lines, inventory counting from shelf images, medical image pre-screening. We build the model, the inference pipeline, and the alert system. One client reduced manual inspection time by 73% within the first quarter of deployment.
A model is only as reliable as its data feed. We design ingestion, cleaning, and feature-engineering pipelines that run on schedule or in real time. Airflow, Spark, dbt, or plain Python scripts: whatever fits the scale. We also audit existing pipelines for drift and silent failures.
We containerise models, set up CI/CD for retraining, configure monitoring dashboards, and write the runbooks your ops team needs. Kubernetes, AWS SageMaker, or bare-metal GPU servers: we deploy where it makes sense for your budget and latency requirements.
Already have models in production? We audit performance, fairness, and cost. Where are you overspending on GPU hours? Which features contribute nothing? We deliver a written report with prioritised recommendations, not a slide deck full of buzzwords.
Three recent projects that illustrate how we work. Details are anonymised where client agreements require it.
Replaced a manual inspection bottleneck with a real-time vision model running on edge GPUs. False-positive rate dropped to 1.2%. The line now processes 40% more boards per shift without adding headcount.
Built a fine-tuned transformer that classifies incoming regulatory updates by relevance to specific business units. Processing time per document went from twelve minutes of analyst review to under two seconds of model inference, with 94% agreement against human labels.
A logistics company had a demand-forecasting model that degraded every quarter. We built an automated retraining pipeline triggered by drift detection. Model accuracy now stays within 2% of its initial benchmark, and retraining runs without human intervention.
We follow a five-phase process. Most projects complete in eight to sixteen weeks from kickoff to production handover.
We spend 60 to 90 minutes understanding your problem, data sources, and constraints. No charge for this call.
We review sample data for quality, volume, and bias. You get a written feasibility assessment within five business days.
A working proof-of-concept model with documented performance metrics. Typically delivered in four to six weeks.
Containerised model, API endpoints, monitoring, and CI/CD pipeline. We test under realistic load before handover.
Monthly performance reviews, drift alerts, and retraining runs. You own the model and the code. We stay as long as you need us.
Describe your problem. We reply within one business day with an honest assessment of whether AI is the right tool for it.
16 Clay Lane, Old Wolff Heath, Northern Ireland, KF94 6FU, United Kingdom
Phone: +44 1874 741113
Email: [email protected]
Monday to Friday, 09:00 to 17:30 GMT. We typically respond to emails within four hours during business days.
The first discovery call is free and lasts up to 90 minutes. We will ask you to share sample data or a schema description beforehand so we can make the conversation productive.