We design and build custom AI systems that take the repetitive intake, reporting, and admin work off your team, so your Edinburgh business handles more clients and enquiries without stretching the specialists you already struggle to hire.
Book a Discovery CallEdinburgh carries an unusual weight of high-value work for its size. Asset managers and insurers cluster around the Exchange District and Charlotte Square, fintech and product teams fill CodeBase and the Quartermile, and studios and agencies line Leith Shore. All of it runs on scarce, expensive people, and the University of Edinburgh and Heriot-Watt turn out the AI talent that everyone else is competing to hire. When salaries climb and specialists are hard to keep, the firms that stop burning them on manual admin pull ahead. Custom AI lets a lean Edinburgh team cover support, operations, sales, and reporting around the clock without adding headcount.
While you weigh it up, the firm along George Street or out at Edinburgh Park is already using AI to answer enquiries faster, clear its backlog, and quote before you do. Every month without automation is a month of manual work you are paying full salary for, and ground you give up quietly in a city where regulated finance and fast fintech both move at pace.
We do not sell you a chatbot and leave. We build production-ready systems that solve real problems across your operation.
We shadow how the work really flows, find the manual steps that eat back-office and client-service hours, from onboarding checks to report packs, and rebuild each one as a system that runs itself and only escalates to a person when judgement is actually required.
Autonomous agents that own a task from first touch to resolution, sorting inbound enquiries, drafting the reply, writing back to your records, and moving the case to its next stage, so a small Edinburgh team stops being the bottleneck on routine requests.
Every enquiry gets logged, scored, and chased within seconds of arriving, so a fintech scaleup or a Festival-season tour operator stops losing warm leads to a slow reply or an inbox nobody has time to clear.
Bring client, pipeline, and portfolio numbers together from the spreadsheets and disconnected tools they hide in, and surface them as one live dashboard, so partners and heads of ops act on today’s position instead of last week’s export.
We connect the AI into whatever Edinburgh teams are already running, whether that is Salesforce, HubSpot, Xero, a fund or policy platform, or a Microsoft 365 inbox, so the build reinforces your stack instead of becoming one more disconnected tool.
Once a system is live we keep measuring it, retrain and adjust as your caseload and the rules around it change, and roll it into the next process only after it has proven its worth on the current one.
A tightly scoped automation pays for itself in the hours it gives back. It works through the repetitive intake and reporting queue, keeps going overnight, at weekends, and through the August surge, and hands your expensive Edinburgh specialists their attention back for clients, product, and the compliance calls only they can make. The result is more capacity on the same payroll.
Edinburgh is one of Europe’s largest financial centres and the UK’s biggest asset-management base outside London. Charlotte Square and the Exchange District hold long-established fund managers and insurers, while Edinburgh Park and the Gyle out west anchor the larger banking and pensions operations. Alongside them sits a real tech story: Skyscanner and FanDuel both started in the city, Rockstar North builds its games here, and CodeBase near Lauriston grew into one of the UK’s largest startup incubators.
That mix decides what automation has to handle. A page written for a generic office would miss it. Edinburgh work leans heavily on regulated finance, client reporting, and product engineering, and the people doing it are among the most expensive inputs the business has. We build for that reality rather than for a template.
The repetitive work here has a particular shape. Across asset managers, insurers, and fintechs the same jobs recur: KYC and AML onboarding checks, client and investor reporting, fund fact sheets and RFP responses, claims and policy admin, and support triage for financial products. Professional services and legal teams around the New Town add document-heavy intake and case work, and tourism and hospitality operators carry a booking and enquiry load that spikes hard every August.
Our first build is always the one with the clearest return and the least exposure, typically a single workflow that is both high volume and heavily rule-based, and we get it working in production before touching anything else. An asset manager might open with client-reporting assembly and later fold in RFP drafting, while a fintech might lead with onboarding checks and grow into handling transaction queries.
Hardly any Edinburgh team is on a single platform. Work comes in from the website, a shared Outlook mailbox, the phone, LinkedIn, and referrals from partners, while the records themselves are spread across Salesforce or HubSpot, Xero or Sage, Microsoft 365, and whatever portfolio, policy, or booking tool the sector runs on. An AI layer is only useful if it can both read and update every one of those, which is why so much of a project’s worth lives in the integration work rather than the model on its own.
That connective work is ours to get right, and regulated work raises the bar on it. Financial services and fintech firms answer to the FCA and to Consumer Duty expectations, every business here carries UK GDPR obligations, and enterprise partners will run a security review before anything touches their data. We design around data residency, access controls, and clear human oversight from the first sketch, and we describe how a system supports your obligations rather than promising a regulatory outcome.
Few cities sit as close to the research as Edinburgh. The University of Edinburgh runs one of the largest informatics and AI schools in Europe, its Bayes Centre focuses on data science and AI, and Heriot-Watt hosts the National Robotarium. The regional Data-Driven Innovation programme has openly set out to make Edinburgh a data capital, and that ambition keeps pulling talent and investment into the city region.
That depth cuts both ways for local employers. The talent exists, but the biggest names compete hard for it, and most firms cannot justify a full in-house AI team for a handful of workflows. Bringing in engineers to build the systems and then run them gives you that capability without the hiring race, and leaves your own specialists free for the work only they can do.
Engineering is the whole point of this firm. The CTOs, heads of ops, and compliance leads we build for get a team that talks their language, scopes against the constraints and the regulator they actually answer to, and delivers systems that survive contact with production instead of impressive demos that fall over a week later.
We build around your goals and your numbers, not around whatever is trendy in AI this month.
Real systems you can deploy across departments, not demos that fall apart in the real world.
Every system is tied to an outcome, so you can see exactly what your investment is returning.
From strategy to build to optimisation, we own the whole thing so you do not have to project-manage it.
“They automated our client onboarding and follow-up across the whole team. What used to take our people half a day now happens the moment an enquiry lands.”
“We expected a chatbot. We got a production system that took a full day of manual work off our operations team in Leith, every single day.”
“These are engineers, not hype merchants. Everything they built works, is documented, and keeps improving.”
Book a discovery call and we will look at where AI can save you the most time and money, then show you exactly what we would build.
Book a Discovery Call