AI integration in Edinburgh
Edinburgh's fund managers read for a living. Company filings, broker research, meeting notes, stewardship reports and client letters arrive faster than any team can absorb them, and the analysts' best hours go on finding the relevant paragraph rather than thinking about it. Client reporting has the same problem in reverse: every quarter, a commentary drafted from the same data by hand.
We build AI features for that work: search across your research that cites the source passage, first drafts of commentary that a portfolio manager edits and approves, and permissions that match who is allowed to see what. Every answer shows where it came from, so an analyst can check it quickly. On FM360 we run a weekly summary written by Claude, and the rule we kept is that every figure in it must trace back to a source.
Edinburgh is a money town with a major research university in the middle of it, and its software work reflects both. On one side sit the fund managers, life and pensions firms and banks: Baillie Gifford, NatWest Group's headquarters at Gogarburn, and a long tail of platforms, administrators and wealth managers. On the other side sit the University of Edinburgh's informatics and data science groups, and EPCC, which hosts the national supercomputer ARCHER2 and was chosen in 2025 as home for the next one, with up to £750 million of government funding.
The financial side needs systems that are careful rather than fast. Pension and investment products carry decades of rules, and much of the administration runs on platforms that predate the people maintaining them. Customers expect to see their pot, their charges and their options clearly on a screen, and advisers expect the platform to answer as fast as the one they used yesterday. So the work is usually integration, data, reporting and customer screens around an old core, with every change tested before it ships. Fintechs sit in between, often selling back into those same banks and fund managers.
The university side needs something different: research code that works on a GPU in a lab and has to become a product that works for a paying customer. That gap, between a model that is right and a service that is reliable, is where many spin-outs stall. Hiring is competitive. ITJobsWatch puts the median advertised software engineer salary in Edinburgh at £70,000 over the six months to September 2026, on a smaller sample than London, and the banks and fund managers take many of the experienced engineers.
Working with us from Edinburgh fits the day you already have. Four hours of every working day overlap with yours, set across your morning, so stand-up, review and the decisions that follow happen live with the engineer who writes the code. The rest of the day runs on written updates and pull requests in your own Slack, GitHub and Linear, waiting for you after lunch, with runbooks and architecture notes written as the work goes.
We are the right fit for a defined piece of work, a spin-out's first production system, or a project that needs senior engineers this quarter while your own hiring catches up. Start with a fixed-price two-week piece and judge us on what ships. For agencies, we work white-label under your name, in your repositories and tools.
Four ways this arrives.
A prompt that behaved on twenty hand-picked inputs meets ten thousand real ones. We build the evaluation set from your actual traffic first, so a change can be judged rather than argued about.
Usually a large context sent on every call, or a big model doing a job a small one can do. We measure where the tokens go before recommending anything.
Logging that captures the prompt, the retrieved context, the model version and the output, so a support question has an answer that is not a guess.
A fallback path, a timeout that is shorter than your user’s patience, and a degraded mode that is honest about being degraded.
A weekly maintenance pulse where Claude writes only the prose, checked against a JSON schema and a whitelist of numbers, with a template that takes over when the model fails.
Read the write-up →Asked by Edinburgh teams.
How do you work with teams in Edinburgh?+
Four hours of every working day overlap with yours, set across your Edinburgh morning, so stand-up and code review happen live. We join your calls and work in your tools: Slack, GitHub and Linear. You talk directly to the engineer who writes the code. The rest of the day carries on in pull requests and written updates that are waiting for you after lunch, with runbooks and architecture notes written as we go.
Do you build for Edinburgh fund managers and pensions firms?+
Yes. For pensions and investment platforms we build services around the administration core: APIs that expose what it knows, transfers and switches processed exactly once, and tools for the exception cases that live in spreadsheets today. For fund managers we build investment data pipelines that trace every figure back to its feed, research search that cites its sources, and customer screens that make pots and charges clear.
How does your rate compare to hiring in Edinburgh?+
ITJobsWatch puts the median advertised salary for a software engineer in Edinburgh at around £70,000. Our published rate is $35/hour with a $5,000 minimum, or $5,400 a month for one engineer embedded in your team. There is no recruiting time and no employment overhead, and we can start within days of the first call. A fixed-price two-week piece at $2,800 lets you judge us on output first.
Can you work with a university spin-out?+
Yes, and it is a good fit. Spin-outs usually have strong research code and nobody whose job is running it in production. The research team stays in charge of the science, and we build what surrounds it: the API, the data handling, the deployment and the monitoring. A fixed-price two-week piece fits a grant or accelerator budget, and the code belongs to the company from the first commit.
Will you tell us if we do not need a model?+
Yes, and it happens often. Several requests we have taken turned out to be a search problem, a rules engine, or a form with better defaults. We would rather say that in week one than bill for a year of prompt tuning.
Whose API keys?+
Yours, in your accounts, with the spend visible to you. We never proxy your traffic through infrastructure we control.
What about our data going to a provider?+
We map exactly what leaves your systems and where it lands before anything is wired up. Where that is not acceptable, self-hosted open-weight models on your own hardware are a real option and we will price both.
Do you fine-tune?+
Rarely, and not as a first move. Retrieval and prompt structure fix most of what people bring to us as a fine-tuning problem, at a fraction of the cost and with none of the retraining treadmill.