AI services that get put into practice
Most AI services stop at the pilot. We take ours into daily use. We work the whole span inside one team: the strategy, the execution, and the handover to your people. The ones who write the strategy are the ones who build it, and the ones still there when it is running.
What we do
We map where AI can improve the work you do every day, put a figure on each opportunity, and work out what it would take: your data, your tools, and who has to work differently. You leave with a list ranked by your business plan rather than by what is technically easiest. The top of the list is what is worth most to you, not what we would most like to build next. This first step is priced to stand on its own, and you own what comes out of it.
- AI Healthcheck & Opportunity DiscoverySee where AI would pay in your business, ranked. The usual way in.
- AI Use Case DiscoveryTake the use cases you are considering and test each one for business impact and feasibility before you commit.
- AI Maturity AssessmentFind out how far your data, tools, skills and governance are from running AI in production.
- AI Governance & Operating ModelDecide who owns AI, which decisions move and which stay, and how you meet the EU AI Act.
A standing team of our engineers, data scientists and strategists works inside your organisation on one of your growth targets. Every cycle ends the same way: a working solution in front of real users, and your decision to scale it or stop paying for it.
- Rapid PrototypingPut a working solution in front of real users within weeks.
- Experiment DesignBuild each experiment around a number you already report, so the result is a decision rather than an opinion.
- Content & Creative AutomationProduce marketing assets with generative AI inside the workflow your team already uses, with your tone of voice and your approval step still in it.
The layer above the other five: who decides what gets funded, and who stops it. Most companies have more AI ideas than they can fund and no honest way to choose between them. We embed a business transformation lead in your organisation who builds the office and runs it, then hands it to the person who will keep it. What stays is an operating model rather than a reporting line: every initiative has an owner, a budget it answers to, and someone who can end it. The office runs on live data from the tools the work already lives in, not on a status meeting.
- An Embedded AI LeadPut a business transformation lead inside your organisation who builds the office, runs it, and hands it over.
- Big Bets & BudgetDecide what share of the AI budget goes on big bets and what share on everyday improvement, then hold that split when the requests start arriving.
- Portfolio & AI BoardPut every initiative through one forum that decides what starts, what moves into development, what goes into management and what stops.
- The AI ToolboxGive your people a short list of approved tools and what each one is for, instead of forty tabs and a policy nobody reads.
- Adoption & AI ChampionsChange how the work is done, not just what people know about AI: champions in each part of the business rather than a central team everyone queues behind.
Give the repetitive half of the processes your teams run every day to AI, and keep the judgement with your people. It runs inside the tools they already work in, so nobody learns a new system, and repetitive steps that took days take minutes. Then your people run it without us.
- Workflow RedesignFix the process first, so you are not paying to run a bad one faster.
- Agentic AutomationHand routine tasks to AI agents that work inside the tools your teams already use.
- Service & Support AutomationAnswer more customer questions automatically and cut what reaches your support team.
- Training & HandoverTrain your people to run and extend the solutions, so the automation outlives the project.
The same execution work, aimed at a decision rather than a process. Models trained on your own data to improve something you already decide many times a week: what to stock, what to charge, which lead to call first. We build the model, the pipeline and the monitoring, then hand all three to your team.
- Forecasting & DemandForecast demand accurately enough to change what you buy, price and hold.
- Propensity & Lead ScoringPut your sales team on the leads most likely to convert and keep the rest off their list.
- Recommendation & PersonalisationShow every customer the products and content most likely to be relevant, in every channel.
- MLOps & MonitoringKeep the model accurate after go-live, with monitoring, retraining and documentation your team can follow.
Many of the AI projects we are called into turn out to be data projects. Our data engineers build the platform your AI runs on: where the data sits, how it moves, and who is allowed to use it.
- Data & Cloud ArchitecturePut your data somewhere secure, governed and fast enough for AI to use.
- Data Platform BuildGet a data platform your own engineers can run and extend without us.
- Customer Data ActivationPut customer data to work in the channels where you sell.
- Pipelines & GovernanceMove data reliably, under clear rules, with a log of every change.
Cases
