LLM integration services UK teams can actually ship: we wire Claude, GPT and open models into your product and operations, with grounding, evals and guardrails, not a thin wrapper around an API key.
Piping a prompt to an endpoint and rendering the reply looks like an AI feature for about a week. Then it hallucinates in front of a customer, the bill spikes on a busy day, and nobody can explain why an answer changed. The hard part is everything around the model, and that is exactly what a wrapper skips.
Teams pick a model on hype, then pay premium rates for a task a cheaper one does just as well, or ship a slow one where latency kills the feature. Model choice is an engineering decision about accuracy, cost, latency and privacy, made per task, not a brand loyalty contest.
Without grounding, the model invents. Without cost controls, usage compounds silently. Without the right data terms, your prompts may be training someone else's model. Each of these is a production incident waiting to happen, and none of them show up in a demo.
We integrate LLMs into real production software, with RAG grounding, evals, guardrails, fallbacks and cost controls built in.
See what you get →Every build ships with the same core package. It is the baseline any LLM integration services UK businesses pay for should meet, whether it powers a product feature or an internal workflow.
Claude, GPT, and open-weight models tested against your real task on accuracy, latency, and cost per call, so the choice is evidence, not a guess.
Retrieval over your own data so the model answers from your content and cites it, instead of inventing plausible-sounding fiction.
A test suite for model outputs, so a prompt change or model upgrade cannot quietly break behaviour you rely on.
Input and output validation, refusal behaviour for out-of-scope requests, and graceful fallbacks when a provider is slow or down.
Caching, model routing, token budgets, and per-feature cost tracking, so the inference bill stays predictable as usage grows.
Prompt tuning, eval maintenance, and model-drift monitoring after launch, from the team that built it.
If any of these describe you, we will tell you on the first call rather than waste your time or ours.
Founder at Seconddate
Foundry 5 really impressed me with their work on my AI-powered dating app. They nailed the UI/UX, starting with core app screens and then translating that vision to the web. The React site they built is sleek and polished - exactly what I was hoping for. What I appreciated most was their thoughtful approach and how easy they were to work with. They got the job done without needing me to micromanage.
CEO at StreaksAI
Foundry 5 surpassed all expectations in delivering our web development product swiftly and flawlessly. Their speed and eye for detail, especially under tight time constraints, showcase their commitment to excellence.
CEO, Xcelsior Capital
Working with Foundry 5 has been a great experience from start to finish. They seamlessly translated our vision into a website that not only showcases our brand and operations but also enhances our online presence as an investor in natural resources. Nothing was too much for them and they always put the client first.
CEO of Ove
Working with Foundry 5 to create the Ove app has been an absolute pleasure. Their professionalism, work ethic, and willingness to always go the extra mile has really impressed me. I would recommend them to anyone.
Loom Founder
Foundry 5 have gone above and beyond to bring my vision of Loom to life. Not only this, but they continue to be an integral part of our team. They are lovely people to work with, and I recommend them to anyone looking for a software partner. Particularly for non-technical tech founders (like me!) who need to ensure that their business is in safe hands.
Chief Product Officer Gather
The team has been instrumental in driving both the design and development of Gather, pairing a proactive, highly responsive workflow with the technical depth needed to handle our platform's complexity. Their partnership continues to move the product forward in a reliable and impactful way.
| Feature | Foundry 5 | Thin wrapper | In-house |
|---|---|---|---|
| Model chosen on benchmarked evidence | |||
| RAG grounding on your own data | |||
| Evals and regression testing | |||
| Guardrails and fallbacks | |||
| Cost controls and monitoring | |||
| No provider lock-in | |||
| You own the code and can extend it | |||
| Honest advice on where an LLM fits |
Pricing for LLM integration services UK founders can plan around: we scope the work, agree a price, and stick to it. No surprise invoices and no scope creep charges. You get a written scope document before code starts, and you own the integration outright once it is live.
For AI features that grow: new models, new use cases, new surfaces in the product. You reprioritise at the start of each sprint as you learn what actually moves the numbers.
Anything else? Just book a call. We'd rather talk than write another FAQ entry.
✓Risk-free first project · Full refund if you’re not satisfied
Whichever one wins on your task, and often it is more than one. We benchmark the candidates against your real inputs and measure accuracy, latency, and cost per call. Claude and GPT are strong general models with different strengths; open-weight models like Llama and Mistral make sense when cost, data residency, or self-hosting matters. We frequently route between models — a cheap one for easy cases, a stronger one for the hard ones — because that is usually cheaper and better than committing to a single provider.
Hallucination is contained with retrieval-augmented generation, output validation, and confidence checks, so answers come from your content and the system knows when to refuse rather than guess. Data leakage is handled by using providers under agreements that prohibit training on your data, documenting exactly what is sent and retained, and running open models in your own environment when a use case demands it. We also test with adversarial and prompt-injection inputs before launch.
Connecting a model — Claude, GPT, or open-source — into your app, workflow, or data so it does useful work: chat, search, summarisation, drafting, support, or agent-style actions. Doing it properly means grounding the model in your data, adding evals and guardrails, building fallbacks and cost controls, and wiring it into your existing systems through APIs, streaming, and tool calling. The model is the small part; the engineering around it is the integration.
Yes. Most of our LLM work goes into products and internal tools that already exist. We connect to your current APIs, database, and authentication, and expose the AI feature wherever your users already are. It behaves like a native feature of your system — versioned, tested, and owned by you — rather than a separate tool bolted on.
Caching, prompt optimisation, model routing, and token budgets, with per-feature cost tracking from day one. We route easy requests to cheaper models and reserve premium models for the cases that need them, so you can see exactly what each feature costs. Nobody should be surprised by their inference bill at the end of the month.
No, and we design against it. We keep the model behind an abstraction so you can switch providers or add a new one without rewriting your product, and the eval suite lets you compare a new model against the current one safely. Avoiding lock-in is one of the main reasons to have the integration engineered properly rather than hard-wired to a single API.
A focused feature is typically two to three weeks from scope to live. A larger integration with RAG grounding, evals, and multiple surfaces runs four to eight weeks. We agree the timeline in writing before any code, and you see a working prototype benchmarked on your real inputs in week two or three, before you commit to the full build.
Book a 30-minute LLM scoping call. No pitch. We will tell you whether the LLM integration services UK teams like yours need are worth building here, which model fits, and how to ship it without the hallucination, cost, and lock-in traps.
✓Risk-free first project · Full refund if you’re not satisfied
