Pure AI Vantage
"We replaced three months of manual data reconciliation with a model that runs in forty seconds. The team now spends that time on strategy instead of spreadsheets."
— Finance director, Belfast-based logistics company, after a six-week engagement with Pure AI Vantage
29
Production models deployed since 2022
6 wk
Median time from brief to live model

Artificial Intelligence services for firms that have outgrown generic tooling

Most mid-market companies hit the same wall. Off-the-shelf AI products promise broad capability, but they bend poorly around the specific data shapes, compliance requirements, and operational rhythms of a real business. That gap between promise and production is where we work.

Pure AI Vantage is a small, senior team based in Northern Ireland. We build, deploy, and maintain custom AI systems. Not prototypes. Not dashboards that look impressive in a demo and then sit idle. Working models, connected to real data pipelines, monitored in production, and handed over with documentation your internal team can actually use.

Our clients tend to arrive after a failed experiment. Perhaps an internal data science hire built a promising notebook model that never made it past staging. Perhaps a large consultancy delivered a strategy deck but no runnable code. We pick up from wherever the last attempt stalled and move the work into production.

Data engineering team reviewing neural network architecture in a Belfast office

Where the work happens

Our engineering room in West Hahnborough. Most projects start here with a data audit before any model code is written.

Capability map

We organise our work into four practice areas. Each can be engaged independently or as part of a longer advisory relationship.

Practice area What we deliver Typical duration Ongoing support
Data strategy and audit Gap analysis of existing data assets, pipeline architecture plan, governance framework, data quality scoring 2–3 weeks
Custom model development Purpose-built machine learning or deep learning models trained on your data, validated against your KPIs, deployed to your infrastructure 4–8 weeks
Automation pipelines End-to-end workflows that connect AI outputs to business systems: CRM enrichment, invoice processing, anomaly alerts, demand forecasting feeds 3–6 weeks
AI advisory retainer Monthly strategic reviews, model performance monitoring, drift detection, retraining schedules, vendor evaluation, team coaching Rolling quarterly Included

How an engagement unfolds

01

Diagnostic call

A forty-minute video call where we learn your data landscape, current tooling, and the business outcome you want the AI to drive. No slides. No pitch. Just questions.

02

Data audit and scope document

We review a sample of your data, assess quality and volume, and produce a scope document that names the model type, success metric, infrastructure requirements, and a fixed-fee quote.

03

Build, validate, deploy

Engineering happens in weekly sprints. You see working outputs each Friday. We deploy to your cloud or on-premise environment and run a parallel validation period before the model goes live.

04

Handover and monitoring

Full documentation, a recorded walkthrough for your team, and optional ongoing monitoring. We set up drift alerts so you know when a model needs retraining before performance degrades.

05

Quarterly review

For retainer clients, we run a quarterly review that covers model health, new data opportunities, and whether the original business case still holds. Priorities shift; models should shift with them.

Real-time analytics dashboard on a laptop screen

Case snapshot: demand forecasting for a regional wholesaler

A food wholesaler operating across twelve depots in Northern Ireland and Scotland was losing margin to over-ordering perishable stock. Their ERP system held three years of order history, but nobody was using it predictively.

We built a gradient-boosted regression model that forecasts demand per SKU per depot for the coming seven days. The model ingests daily sales data, weather feeds, and calendar events. After ten weeks in production, spoilage costs dropped by 18% and reorder accuracy improved enough that two part-time stock-checking roles were redeployed to customer service.

Engagement length: 5 weeks build, ongoing monthly monitoring

Is this a good fit?

We are selective about the projects we take on. Here is an honest breakdown of where we add the most value and where you might be better served elsewhere.

Strong fit

You have at least six months of structured business data. You can name the decision or process you want the AI to improve. Your team includes someone technical enough to own the model after handover.

Possible fit

You have data but it lives in disconnected systems. You are not sure which problem to tackle first. In this case, we usually recommend starting with a paid data audit before committing to a full build.

Not the right fit

You are looking for a chatbot plugin, a generic content generator, or a product that works out of the box without configuration. Those exist and are often cheaper than custom work. We can point you to good options.

Questions we hear in most diagnostic calls

No. We work within your existing infrastructure. If your data is in Azure, AWS, Google Cloud, or an on-premise server, we develop and deploy there. We never require data to leave your environment. During the audit phase, we may ask for a sanitised sample to test feasibility, but that is always optional and governed by a data processing agreement you control.
A data audit starts at £2,400. A full model build ranges from £8,000 to £25,000 depending on complexity, data volume, and integration requirements. Advisory retainers are priced quarterly. We always provide a fixed-fee quote after the diagnostic call so there are no surprises.
Yes, and we prefer it. The best outcomes happen when your internal people are involved from day one. We pair-programme where practical, run knowledge-transfer sessions, and write documentation aimed at your team rather than at us. The goal is always to reduce your dependency on external help over time.
We define a measurable success metric in the scope document before any build work starts. If the model fails to meet that metric after a reasonable validation period, we either iterate at no extra charge or refund the build fee. This has happened once in 29 deployments, and in that case the root cause was insufficient training data, which we flagged as a risk during the audit.
Every engagement starts with a data processing agreement. We follow UK GDPR requirements, apply data minimisation principles, and never retain client data beyond the active project unless explicitly agreed. Models that process personal data include audit logging and consent-aware processing paths.
"They told us upfront that our dataset was too small for the approach we wanted. Instead of selling us something that would fail, they recommended a simpler rule-based system and helped us build it in two weeks. That honesty is rare."
— Operations manager, Derry-based healthcare logistics firm

Start with a diagnostic call

Fill in the short form and we will reply within one working day to schedule a forty-minute video call. No obligation, no sales deck. We want to understand your data and your problem before we talk about solutions.

+44 7193 759999

[email protected]

49 Hall Lane, West Hahnborough, Northern Ireland, BC8 1HL, United Kingdom

Thank you. We will be in touch within one working day.

Legal and policy information

Data we collect

When you submit the inquiry form, we store your name, email address, selected service interest, and message text. We also collect basic analytics data (pages visited, time on site) through cookies.

How we use it

Your inquiry data is used solely to respond to your request and, if you become a client, to manage the engagement. Analytics data helps us understand which parts of this site are useful and which are not. We do not sell, rent, or share personal data with third parties except where required by law.

Retention

Inquiry data is kept for twelve months after last contact, then deleted. Analytics cookies expire after ninety days.

Your rights

Under UK GDPR, you can request access to, correction of, or deletion of your personal data at any time by emailing [email protected]. We will respond within thirty days.

Last reviewed: January 2026.

Scope

These terms govern your use of the pureaivantage.cyou website and any preliminary communications initiated through it. Formal project engagements are governed by a separate statement of work and data processing agreement.

Intellectual property

All content on this site, including text, graphics, and code, is the property of Pure AI Vantage unless otherwise stated. You may not reproduce it without written permission.

Limitation of liability

Information on this site is provided for general guidance. We make reasonable efforts to keep it accurate but accept no liability for decisions made based on site content alone. Professional advice should be sought for specific situations.

Governing law

These terms are governed by the laws of Northern Ireland and the United Kingdom.

Last reviewed: January 2026.

Case studies and performance figures cited on this site reflect specific client engagements and are not guarantees of future results. AI model performance depends on data quality, volume, and the business context in which the model operates. We provide realistic expectations during the diagnostic phase and define measurable success criteria before any paid work begins.

Pure AI Vantage is not a regulated financial, legal, or medical advisory firm. Our services relate to data engineering and machine learning. If your use case involves regulated data or decisions, we will recommend involving the appropriate domain specialists.

Last reviewed: January 2026.

This site uses a small number of cookies for analytics and to remember your preferences. See our privacy policy for details.