We don't sell AI as a concept. We build models that sit inside your operations, trained on your data, measured against your revenue targets. Three recent engagements tell the story better than any pitch deck.
£2.3m in recovered revenue across 2024 client portfolio— Head of supply chain, a Scottish food distributor (engagement began March 2024)
Each engagement started with a question the client couldn't answer from their existing dashboards. We scoped, built, and handed over production-grade models — not prototypes.
A Clyde-based operator was losing £18k per unplanned engine shutdown. We ingested two years of sensor telemetry, trained a gradient-boosted classifier on failure-precursor patterns, and deployed an alert pipeline to their engineering team's tablets.
Tenant complaints arrived via email, web form, and letter. Staff spent 14 hours a week routing them manually. Our transformer-based classifier now reads every inbound message, assigns a category and urgency score, and pushes it to the right team in under four seconds.
A Borders-region printer was catching colour-registration defects only at the end of a 40-metre roll. We mounted cameras at three points on the line and trained a YOLO-family detector on 6,200 annotated defect images. Defects are now flagged within 1.2 metres of occurrence.
We work across four AI domains. The table below maps each one to the typical business question it answers, the data it needs, and the delivery format you receive.
| Domain | Business question | Data requirement | Delivery |
|---|---|---|---|
| Predictive analytics | When will this asset fail? How much will we sell next month? | 12+ months of timestamped operational or transactional records | REST API endpoint + dashboard integration |
| Natural language processing | What are customers actually saying? Which emails need urgent action? | Corpus of 2,000+ labelled text samples (we help you label) | Classification microservice or batch pipeline |
| Computer vision | Is this product defective? Can we count inventory automatically? | 1,500+ annotated images (we supply annotation tooling) | Edge-deployed model or cloud inference API |
| Recommendation engines | Which products should this customer see next? | User interaction logs — clicks, purchases, ratings | Real-time scoring API integrated with your platform |
No two projects look the same, but every one follows the same accountability structure. Here's the typical arc from first call to production handover.
60-minute session. We map your data landscape, identify the highest-value prediction target, and agree whether AI is even the right tool. Sometimes it isn't — we'll say so.
We connect to your systems read-only, profile the data, and produce a feasibility memo within five working days. Fee: £1,200, credited against any subsequent build.
Iterative build in two-week sprints. You see metrics after each sprint — precision, recall, business-relevant accuracy — and decide whether to continue.
We containerise the model, deploy it to your infrastructure (or ours), and set up drift alerts. You own the code and the weights.
Optional retainer for retraining, feature expansion, and performance reviews. Most clients retrain quarterly.
Not every company needs bespoke AI. We've turned down projects where a well-configured spreadsheet would do the job. Here's how to gauge whether a conversation with us is worth your time.
The data audit takes about a week. Model development runs four to ten weeks depending on complexity. A straightforward classification model might ship in five weeks; a multi-signal forecasting system with real-time inference can take three months.
Yes. Every deliverable — source code, trained weights, documentation — transfers to you under a perpetual licence at project completion. We retain no lock-in.
We've deployed to AWS (SageMaker, ECS), Google Cloud (Vertex AI, Cloud Run), and Azure (AML, AKS). If you run on-premise Kubernetes, that works too. We match your existing infrastructure.
We set a minimum accuracy threshold during scoping. If the model doesn't hit that threshold after two sprint cycles, we stop and you pay only for completed sprints. We've paused two projects this way — both times the root cause was insufficient training data, and we helped the client build a labelling programme before re-engaging.
Describe the decision you want to automate or improve. We'll reply within one working day with an honest assessment of whether AI can help.
Precision AI Insights collects personal data (name, email, company, message content) only when you submit the inquiry form on this site. We use this data solely to respond to your inquiry and, if you consent, to send occasional updates about our services. We do not sell, rent, or share your data with third parties except where required by UK law. Data is stored on encrypted servers within the European Economic Area. You may request access to, correction of, or deletion of your personal data at any time by emailing [email protected]. We use a single cookie to record your consent preference for this notice; no tracking or analytics cookies are deployed. This policy was last reviewed in January 2026.
By using this website you agree to these terms. The content on precisionaiinsights.cyou is provided for general information about our artificial intelligence consulting services. It does not constitute a contractual offer. Engagement terms, deliverables, timelines, and fees are agreed separately in a signed statement of work for each project. Precision AI Insights retains the right to decline any engagement at its discretion. All intellectual property created during an engagement transfers to the client upon full payment, as specified in the relevant statement of work. We are not liable for decisions made on the basis of information published on this website. These terms are governed by the laws of Scotland.
Case study results described on this site reflect outcomes achieved for specific clients under specific conditions. Past performance does not guarantee similar results for future engagements. Model accuracy, deployment timelines, and financial impact depend on data quality, volume, and the operational context of each client. Precision AI Insights makes no warranty, express or implied, regarding the suitability of artificial intelligence for any particular business problem. The discovery call and data audit stages exist precisely to assess feasibility before committing to a full build.