AI consultancy & engineering · United Kingdom
We are an AI consultancy that builds the thing, not just the deck. From readiness assessment and roadmap through to models running in production — large language models, computer vision, NLP and edge AI, engineered to survive real load.
What we do
Most agencies hand you a strategy and leave. Most dev shops build without a strategy. We do the whole arc — and the boring infrastructure half that decides whether any of it survives contact with production.
Before a line of model code is written, we work out whether AI is the right answer at all — and where it pays back fastest. You get a clear-eyed view of your data, your systems and your team, and a roadmap you can actually fund.
We build the thing. Models trained on your data, wired into the systems you already run, tuned until the latency and accuracy numbers hold up under real load rather than in a notebook.
The unglamorous half that decides whether a model survives contact with production. Pipelines, monitoring, retraining, access control and a cost curve that does not surprise your finance team.
Technical expertise
Six disciplines we work in daily. Each one is a practice, not a bullet point on a capabilities slide.
Custom LLM development, enterprise-grade generative AI, multimodal systems, content generation and analysis, AI-powered creative tools, and responsible AI implementation.
Edge model optimisation, real-time processing, IoT integration and analytics, low-latency applications, energy-efficient deployment and edge-cloud hybrid architectures.
Custom deep learning models, neural architecture design and optimisation, production-ready ML systems, and performance optimisation and scaling.
Image recognition and processing, real-time object detection and tracking, video analytics and surveillance, medical imaging analysis, and quality control automation.
Custom language models, multilingual systems, intelligent document processing, conversational AI, and sentiment and text analytics.
End-to-end AI system design, MLOps implementation and automation, cloud infrastructure optimisation, and scalable AI pipeline development.
Industry solutions
A fraud model and a defect-detection model share more architecture than either team expects. What differs is the regulation, the tolerance for false positives, and what happens when the system is wrong.
Quality control automation, predictive maintenance, process optimisation and supply chain intelligence.
ExploreMedical image analysis, patient data analytics, treatment prediction and healthcare workflow optimisation.
ExploreRisk assessment models, fraud detection, trading algorithms and customer analytics.
ExploreCustomer behaviour analysis, inventory optimisation, visual search, recommendation engines, dynamic pricing, virtual try-on and demand forecasting.
ExploreContent recommendation, AI-powered content creation, engagement analytics, real-time moderation, virtual character generation and interactive gaming AI.
ExploreAdaptive learning platforms, student performance analytics, interactive AI education tools, automated assessment, personalised curriculum generation and virtual lab simulations.
ExplorePlant health and stress reporting, nitrogen requirement mapping, plant counting, harvest monitoring, water stress analysis and crop classification.
ExploreSelected work
Four projects, four different problems. Each one went from a client conversation to something running against real data.
StreamFlow Media needed an advanced recommendation system to lift engagement on their streaming platform. We built RecoMax, a recommendation engine that learns from viewing behaviour in real time.
UrbanGuard Security required intelligent surveillance across high-traffic urban areas. SecureVision applies computer vision to live camera feeds, surfacing events as they happen rather than after the fact.
FinTech Innovators wanted to read market sentiment from financial news and social media. MarketSentiment turns unstructured text into a signal their analysts can act on.
CallTech Solutions needed to understand what was actually happening on their calls. AudioIQ analyses call-centre audio at scale, turning conversations into structured operational insight.
Our presence
Our office is in Oldham, Greater Manchester. Our work is not — we deliver for clients across the United Kingdom and internationally, remotely and on site.
Oldham, United Kingdom
Companies we have worked for
How we work
The same sequence every time, because it is the sequence that stops AI projects dying at the demo stage.
We start by getting deep into your business — the workflows, the data you actually hold, and the problem worth solving first.
Our team designs a solution around your specific constraints, not a template. Architecture, data flow and success measures agreed up front.
We build robust, scalable systems using current tooling, with evaluation baked in from the first iteration rather than bolted on at the end.
Smooth implementation and integration with the systems you already run, with rollout staged so nothing breaks in production.
Ongoing support, monitoring and optimisation — because a model that is never retrained quietly degrades.
Why VertexAI
Deep expertise in current AI technologies and engineering practice, so what we hand over is robust and future-proof.
We understand the constraints particular to each sector and tailor solutions that deliver real business value.
From first consultation to deployment and maintenance, we stay your partner across the whole implementation.
We track the edge of AI advancement and bring current methods to bear on your business problems.
Client voices
“The integration of VertexAI's computer vision technology into our security systems has greatly enhanced our surveillance capabilities. Their innovative solutions have provided us with real-time insights and improved our overall safety measures.”
“Working with VertexAI has been a game-changer for our business. Their customised machine learning algorithms have enabled us to predict market trends with remarkable accuracy, leading to significant growth and profitability.”
“The team at VertexAI is phenomenal. They fine-tuned state-of-the-art language models for our specific industry needs, resulting in highly effective conversational AI applications.”
“VertexAI's natural language processing tools have revolutionised our customer service. Their chatbots and virtual assistants have significantly improved user engagement and satisfaction.”
“VertexAI's AI-powered mobile applications have taken our user experience to the next level. The personalised recommendations and real-time analytics have greatly enhanced our app's performance.”
“The predictive analytics and forecasting solutions provided by VertexAI have been invaluable to our decision-making. We can now anticipate trends and make data-driven decisions with confidence.”
Questions
If yours is not here, ask it directly — the form below reaches a person.
Most engagements begin with an AI readiness assessment: we look at your data, systems and team, identify the use cases with the clearest return, and produce a roadmap. From there we design, build, deploy and support the solution — you can bring us in for the whole arc or for a single stage.
No. Many of our clients have strong engineering teams but no dedicated ML capability. We work alongside your existing developers, handle the AI-specific engineering, and document and hand over the system so your team can own it afterwards.
We deliver industry-specific AI across manufacturing and Industry 4.0, healthcare and medical, financial services, retail and e-commerce, entertainment and media, and STEM education. The underlying engineering transfers; the domain constraints are what we tailor.
Yes. AI infrastructure design is one of our core services and covers cloud AI architecture, MLOps implementation, scalability planning and security. We design around your hosting, data residency and compliance requirements rather than imposing a stack.
Off-the-shelf models are a sensible starting point and we use them where they fit. Custom development matters when your data, latency budget, accuracy threshold or domain language make a general-purpose model insufficient — which is typically where we are brought in.
Responsible AI implementation is part of our generative AI practice, and security implementation is built into our infrastructure work. We agree data handling, access control and evaluation criteria at the design stage, and monitoring continues after deployment.
Let’s build
Whether you have a defined project or just a suspicion that AI should be doing something in your business, start the conversation. We will tell you honestly whether it is worth doing.