We design, train and deploy machine learning systems for mid-sized companies across Scotland and the rest of the UK. No generic chatbots. No dashboards you will never open. Just models that do a specific job, measured by the money they save you.
Talk to our engineers about your dataEach engagement starts with your data, not our product catalogue. Here are the four areas where we deliver the most measurable results.
We build regression and classification models on your historical records. A logistics client in Glasgow reduced late deliveries by 31% within three months using a demand-forecasting model we trained on two years of order data. The model runs nightly, re-scores every route and flags the ten highest-risk shipments before the morning shift starts.
Ticket classification, document extraction, sentiment scoring. One insurer we work with processes 4,000 claims emails per day. Our NLP pipeline reads each one, extracts policy numbers, damage descriptions and claimant details, then routes the case to the right handler. Manual triage dropped from 22 minutes per claim to under 3.
Quality inspection, defect detection, safety monitoring. We trained a convolutional network for a packaging manufacturer that checks seal integrity on 800 units per minute. False-positive rate sits below 0.4%, which means the line stops only when something is genuinely wrong.
A model is only useful if it runs reliably in production. We set up training pipelines, monitoring dashboards, drift detection and automated retraining schedules. If your data lives in spreadsheets today, we will help migrate it to a proper warehouse first. No point building a neural network on top of a folder full of CSVs.
Five stages, each with a clear deliverable. You approve before we move on.
We review what you collect, where it lives and how clean it is. Takes one to two weeks.
We agree on the metric that matters: cost saved, time freed, errors prevented. One metric, not twelve.
A working model on a sample of your data, tested against a hold-out set you can inspect.
Containerised, monitored and integrated with your existing systems via API or batch job.
Monthly performance reports, retraining when drift is detected, priority access to our engineering team.
Big firms send a partner to the pitch and a graduate to the project. We do not operate that way. The engineer who scopes your system is the same person who writes the training code and answers your calls six months later.
We are a team of nine, based in Scotland. Every one of us has shipped production ML before joining. That small size means lower overhead, faster decisions and a genuine stake in your results.
Pricing is project-based with a fixed ceiling, not time-and-materials. You will never get a surprise invoice because a data cleaning step took longer than expected.
Answers based on what prospective clients actually ask us on first calls.
It depends on the task. A tabular classification problem can work well with a few thousand rows. Computer vision typically needs several hundred labelled images per class. During the data audit we will tell you honestly whether you have enough, and if not, what the cheapest way to collect more looks like.
Yes. About a third of our clients are elsewhere in the UK, and we have two ongoing projects with firms in the Netherlands. All collaboration happens over video calls and shared repositories. We visit on-site for the initial data audit when the project budget allows it.
We agree on a minimum performance threshold before the prototype stage. If the model cannot hit that bar after two rounds of iteration, we stop and you pay only for the work completed up to that point. This has happened twice in four years. Both times the root cause was data quality, and we helped the client fix the underlying collection process so they could revisit the project later.
We deploy models behind a REST API or as a scheduled batch process. If your stack runs on AWS, Azure or GCP, we deploy there directly. For on-premise setups we containerise with Docker and provide a Helm chart. We have integrated with SAP, Salesforce, Dynamics 365 and various bespoke ERPs.
All data stays within your own cloud tenancy or on-premise infrastructure. We access it through temporary credentials with audit logging. For healthcare and financial services projects we follow ICO guidance on automated decision-making and can prepare the documentation your compliance team needs for a DPIA.
Describe the problem you want to solve. We will reply within one working day with an honest assessment of whether AI is the right tool for it.
4 Lillian Drive, Long Handhill, Scotland, GW3 9TR, United Kingdom