The AI software that learns your business before you explain it

We build intelligent systems that observe, adapt, and act — turning messy operational data into measurable commercial gains. No generic dashboards. No buzzword bingo. Just software that works harder than the team it supports.

Show me what's possible
Futuristic AI data visualization with flowing neural network connections
0 Models deployed this year
0% Average cost reduction
0 Industries served
0ms Median inference latency

What we actually build

Every engagement starts with your problem, not our product catalogue. That said, most of our work falls into four areas where AI software delivers the steepest returns.

Predictive analytics engines

Time-series forecasting, demand planning, and anomaly detection built on your proprietary data. We handle feature engineering, model selection, and continuous retraining so predictions stay sharp as conditions shift. Typical accuracy gains sit between 18% and 34% over legacy statistical methods.

Document intelligence

Invoices, contracts, medical records, regulatory filings — our extraction pipelines parse unstructured documents at scale. Combining OCR, layout analysis, and large language models, we convert paper-heavy workflows into structured, searchable data within hours of deployment.

Decision automation

Credit scoring, pricing optimisation, resource allocation, triage routing — wherever a human makes the same judgement call hundreds of times a day, we train a model to replicate (and often outperform) that decision. Guardrails and explainability layers come standard.

Conversational AI platforms

Customer-facing chatbots and internal knowledge assistants grounded in your documentation. We fine-tune foundation models, implement retrieval-augmented generation, and build feedback loops that improve answer quality week over week without manual curation.

Evidence, not promises

Three projects. Three industries. Measurable numbers you can verify with a phone call.

North Sea supply vessels near offshore platform

A fleet operator running 14 supply vessels needed to cut fuel spend without adding transit time. We ingested five years of AIS tracking data, weather patterns, and port scheduling records to build a reinforcement-learning model that re-sequences port calls in real time.

£2.1m annual fuel savings

The system paid for itself within eleven weeks and now handles 92% of route decisions autonomously, with human override reserved for severe weather events.

Insurance analysts reviewing claims data on monitors

Manual claims review was costing this mid-market insurer 6.4 FTE hours per straightforward motor claim. We trained a document-intelligence pipeline that extracts policy details, cross-references repair estimates, and flags fraud indicators — routing 71% of claims to auto-approval.

71% auto-approval rate

Average settlement time dropped from nine days to under forty hours. False-positive fraud flags fell by 38% compared to the rule-based system it replaced.

Modern NHS hospital corridor with medical staff

Bed shortages during winter surges were creating four-hour A&E breaches. We built a 72-hour patient-flow forecast using admission patterns, GP referral volumes, and regional flu surveillance data. Ward managers now receive shift-level staffing recommendations each morning.

29% fewer four-hour breaches

The pilot ran across two winter seasons and is now being adopted by three additional trusts in Scotland. The model retrains weekly on fresh admission data to capture emerging seasonal patterns.

How an engagement unfolds

No 80-slide discovery deck. We move fast, prove value early, and scale what works.

01

Data audit

We spend two weeks inside your systems — databases, spreadsheets, APIs, even paper forms — cataloguing what exists, what's missing, and what's usable. You get a frank assessment, not a sales pitch.

02

Proof of concept

A working prototype on real data, delivered in four to six weeks. We pick the single highest-value use case and build just enough to demonstrate measurable impact. If the numbers disappoint, we part ways — no hard feelings.

03

Production hardening

The prototype becomes production-grade: monitoring, fallback logic, security review, load testing. We integrate with your existing stack via REST or event-driven architectures, never forcing a platform migration.

04

Continuous learning

Models drift. Data changes. We set up automated retraining pipelines, performance dashboards, and alerting so your AI software stays accurate months and years after launch — not just on demo day.

05

Knowledge transfer

We document everything and train your internal team to own the system. Our goal is to make ourselves unnecessary. Ongoing support contracts are available but never required.

Questions we hear often

Less than you think. For tabular prediction tasks, a few thousand well-labelled rows can produce useful models. For document intelligence, we often start with as few as 200 annotated examples and use transfer learning to close the gap. The real bottleneck is usually data quality, not quantity — and our audit phase is designed to surface those issues early.
Proof-of-concept engagements range from £25,000 to £60,000 depending on data complexity. Full production builds sit between £80,000 and £250,000. We price on outcomes, not hours — if the model fails to hit agreed KPIs during the PoC, you owe nothing beyond the audit fee.
Yes. We deploy on AWS, Azure, and GCP. For organisations with strict data-residency requirements, we also support on-premises Kubernetes clusters. Our inference pipelines are containerised and cloud-agnostic by design, so switching providers later carries minimal friction.
Every project begins with a Data Protection Impact Assessment. We anonymise or pseudonymise personal data before it enters training pipelines. Model outputs are logged and auditable. We hold Cyber Essentials Plus certification and are happy to work under your existing DPA terms.
Our monitoring layer tracks prediction accuracy, data drift, and feature importance in real time. When performance drops below a configurable threshold, the system triggers an automated retraining cycle and alerts your team. If the drift is structural — say, a market shift — we intervene manually to re-architect the feature set.

Start a conversation

Tell us what you are trying to solve. We will respond within one working day with an honest take on whether AI is the right tool — and if it is, what the first step looks like.

Visit us
346 Fannie Court, East Fadel, Scotland, FS34 3CI, United Kingdom

Call
+44 1834 165337

Email
[email protected]

Aerial view of Scottish town near our office