We build Artificial Intelligence that actually fits your business

Most AI projects stall because they start with technology instead of the problem. We flip that. You tell us where the bottleneck is, and we design a system around it. Prediction models, language processing, document automation: whatever the task, the output is something your team can use on day one.

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AI team collaborating on neural network project in a modern office
140+ AI models deployed
97% client retention rate
6 years in operation
35 industries served

The gap between AI hype and real results

Businesses hear about AI breakthroughs every week, yet most internal pilots never reach production. Here is what we see going wrong, and how we fix it.

Common pain points

  • Proof-of-concept models that never leave the data team's laptop
  • Vendors who deliver dashboards nobody opens after month two
  • Training data scattered across spreadsheets, PDFs and legacy databases
  • Internal teams stretched too thin to maintain a custom ML pipeline

How we address each one

  • Every engagement has a production deployment milestone in the first eight weeks
  • We embed usage tracking so you see adoption, not just accuracy scores
  • Our data engineers build ingestion pipelines that unify messy sources before modelling begins
  • Post-launch support packages include monitoring, retraining and on-call engineering hours

What we deliver

Each service is scoped to a measurable business outcome. We do not sell "AI strategy decks" that gather dust.

Predictive analytics

Demand forecasting, churn prediction, anomaly detection. We train models on your historical data and integrate the output into the tools your operations team already uses, whether that is Salesforce, SAP or a bespoke internal dashboard.

Natural language processing

Chatbots that handle tier-one support queries, document classifiers that route incoming mail, and sentiment analysis for customer feedback. We fine-tune large language models on your domain vocabulary so the system understands jargon from the start.

Workflow automation

Invoice extraction, contract review, quality-control image checks on a production line. We combine computer vision and NLP with RPA connectors so repetitive knowledge work runs without human intervention.

AI readiness assessments

Not sure where to begin? We audit your data estate, interview stakeholders, and produce a prioritised roadmap in two weeks. The output is a concrete list of projects ranked by effort, impact and data availability.

Team training and upskilling

Hands-on workshops for your developers, analysts and product managers. Topics range from prompt engineering and retrieval-augmented generation to MLOps fundamentals. Sessions run over two or four days, on-site or remote.

Four stages from question to production

We keep the process lean. No twelve-month discovery phases.

Scoping

We spend a week understanding your data, your constraints and the metric you want to move. This stage ends with a fixed-scope proposal.

Prototyping

A working model within three to four weeks. You interact with it, stress-test edge cases, and we iterate until accuracy meets the agreed threshold.

Integration

The model connects to your live systems through APIs or batch jobs. We handle authentication, error handling and fallback logic.

Monitoring

Drift detection, retraining schedules and performance dashboards. You get a monthly report and direct access to our engineering team via a shared Slack channel.

A recent project in detail

Warehouse logistics enhanced by AI-powered analytics and sorting

Reducing mis-shipments for a Scottish distributor

A mid-size distributor based near Edinburgh was losing roughly £180,000 a year to incorrect shipments. Their order entry system relied on free-text product descriptions that warehouse staff interpreted differently depending on the shift.

We trained a classification model on two years of order history, mapping free-text entries to standardised SKUs with 98.4% accuracy. The system flags uncertain matches for human review instead of guessing. Within five months, mis-shipment costs dropped by 72%.

"We expected a marginal improvement. Instead, the returns desk went from processing forty cases a week to eleven." Operations director, name withheld by agreement

Questions we hear often

How much data do we need before an AI project is viable?

It depends on the task. A simple classification model can work well with a few thousand labelled examples. Complex forecasting typically needs at least a year of historical records at daily granularity. During the scoping stage we assess whether your data volume is sufficient or if augmentation techniques can bridge the gap.

Do you work with companies outside Scotland?

Yes. About half of our clients are based elsewhere in the UK, and we have delivered projects for firms in Ireland and the Netherlands. Remote collaboration works well for most engagements, though we prefer at least one on-site visit during scoping.

What does a typical engagement cost?

An AI readiness assessment starts at £4,500. End-to-end model development projects range from £15,000 to £90,000 depending on complexity and integration requirements. We quote a fixed price after scoping so there are no surprises.

Will we own the model and the code?

You own all bespoke code, trained model weights and documentation produced during the project. We retain the right to reuse general-purpose tooling and libraries, but nothing specific to your data or business logic.

How do you handle sensitive data?

We sign a data processing agreement before any data transfer. All work happens in encrypted cloud environments hosted in the UK, and we can operate within your own infrastructure if compliance requires it. Personal data is pseudonymised during model training wherever possible.

Let's talk about your project

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Get in touch

Address:
311 Meadow View, Sawaynington, Scotland, FX21 0WG, United Kingdom

Phone:
+44 371 543 8527

Email:
[email protected]