A UK AI agent development company that ships agents into production under FCA, ICO and MHRA rules, with the evaluation harness that proves they work. Senior UK engineers, published GBP rates, no London premium.
The team at Winder.AI are ready to collaborate with you on your AI project. We tailor our AI solutions to meet your unique needs, allowing you to focus on achieving your strategic objectives. Fill out the form below to get started.
An AI agent development company builds software that uses a language model to plan a task, call your systems through tools, check its own results and act, and it ships that software into production with the controls a UK buyer has to show a regulator or an auditor. The job starts before the code: deciding whether the workflow needs an agent at all, since a deterministic pipeline or a classical machine learning model is often cheaper to build and far easier to test. In the UK the engagement usually carries a regulatory overlay too, most often the Financial Conduct Authority (FCA) for financial services, the Information Commissioner’s Office (ICO) for personal data, or the Medicines and Healthcare products Regulatory Agency (MHRA) for clinical software.
Winder.AI has built autonomous systems since 2013 and wrote the O’Reilly book on reinforcement learning, which is the older branch of the same discipline. A reinforcement learning agent we helped a UK consumer-finance lender build went live on real customer traffic in 2023. The AI assistant we built for Temple University’s legal research centre was measured by their team at nearly 80% accuracy at finding the right legal text. Our open-source invoice-triage agent scores 100% field-level extraction accuracy on its held-out set, and the code and results are on GitHub for anyone to re-run. Senior UK engineers do the work, led by Dr Phil Winder, and we price in GBP and publish the rates below.
The UK market splits into six types of provider, and the useful question is which one is the wrong shape for your problem. We publish this page, so our own row sits in the table with its limits stated like everyone else’s. Competitor details were checked on 18 August 2026.
| Provider type | Best for | Where it stops |
|---|---|---|
| Global consultancy or Big-4 practice (Accenture, Deloitte) | Agents as one workstream inside a multi-year transformation, with a name the board recognises on the contract | Transformation pricing for what is often a four-month engineering job, and pyramid staffing: senior pitch, junior delivery |
| UK software house with an agent line (Geeks Ltd in Sutton, Deployflow) | An agent inside a wider software or DevOps programme, with a UK office you can visit | Agents are one page in a catalogue. Both say “transparent pricing”; neither publishes a figure |
| UK automation boutique (Openkit, Flux Technology) | One back-office workflow at a fixed price, £10k to £30k per workflow in their FAQs | Built for a single workflow. Thin on evaluation, and on the record a UK financial or healthcare buyer has to produce for a regulator |
| Platform vendor (ServiceNow with Moveworks, Microsoft Copilot Studio) | Buying a configurable product where the workflow already lives inside the vendor’s tool | You get the vendor’s agent on the vendor’s surface, priced per seat. Bespoke integrations and evaluation stay your problem |
| Offshore delivery with a UK sales office (N-iX) | Headcount for a long programme, once the specification is written and you are sure it is right | The UK presence is commercial and the engineering happens elsewhere. On 14 August 2026 we found no named client with a deployed agent and a measured result on its site |
| Engineering-led UK specialist (Winder.AI) | Bespoke agents in regulated or technical domains where the answer has to be measurably right, and an assessment of whether the agent is worth building at all | Boutique scale. One published agent accuracy metric so far, and a team this size cannot staff a programme of hundreds |
There is no cheap-option row, because cheapness is a size of engagement and every row can be bought small. Ours starts at £15k as a fixed-fee proof of concept with the evaluation harness inside it.
The pattern in the UK agent projects we get called into is the same one we see in language-model work generally. A demo impressed the room. Nothing measured it. So when the production version behaved differently, nobody could say whether it was better or worse than the demo, and the regulator’s question (“show me why it decided that”) had no answer. We build the harness first, and we will tell you when a workflow does not need an agent. In our own engagements that has meant recommending a rule-based pipeline or a fine-tuned small model instead, and we build those too.
The UK has no single AI law, so the constraints on an agent come from the sector regulator and from data protection. Which ones bite depends on what the agent touches.
For financial services the FCA has said it will apply its existing framework to AI, so an agent that talks to customers, triages complaints or feeds a credit decision sits under Consumer Duty, the Senior Managers and Certification Regime and the operational resilience rules. In practice the firm needs to explain what the agent did in a given case, prove that a person could intervene, and show the testing that was done before it went live. We have worked under those expectations with an FCA-regulated car-finance lender and with the UK consumer lender above.
For personal data the UK GDPR governs, and the Data (Use and Access) Act 2025 loosened the rule on solely automated decisions with significant effects: they are now permitted for ordinary personal data provided the person is told, can contest the outcome and can get a human review. That maps directly onto agent design. The approval gate, the audit trail and the “why” the agent records are the safeguards, so we build them into the tool layer from the first week.
For healthcare and life sciences the MHRA treats qualifying AI as software as a medical device, and an agent that suggests a clinical action can qualify. For central government the Algorithmic Transparency Recording Standard requires a published record of the tool and how it is used, and the assurance evidence an accounting officer needs before sign-off. Ofcom, the UK communications regulator, commissioned us to write its report on automated content classification, so we have sat on the regulator’s side of that table as well as the supplier’s. A UK group selling into the EU inherits the EU AI Act on top, and that overlay is covered by our AI governance consulting practice.
We publish rates because withholding them wastes everybody’s first call.
| Engagement | Duration | Indicative Winder.AI cost |
|---|---|---|
| Scoping and agent-fit assessment: does this workflow need an agent, and what would it look like | 2 to 4 weeks | Fixed fee, low five figures GBP |
| Proof of concept: one workflow, one system integration, an evaluation harness | 4 to 8 weeks | £15k to £40k fixed fee |
| Production build and operations | Ongoing | £150 to £300 per hour on time and materials |
| Retained specialist consulting | Ongoing | £350 per hour, £5k per month minimum |
The UK automation boutiques in the table above publish £10k to £30k per workflow. Our proof-of-concept range starts higher because the harness that proves the agent works, and the record a regulated buyer needs, are inside it. Worked examples from real projects are on the pricing page, and the wider UK market is in our AI consulting cost guide.
There is no London premium. We are remote-first and go on-site where the work pays for the travel. What the rate buys is the running agent and the evidence that it works, which is the thing a UK regulator will ask for.
Their expertise and knowledge in the AI and MLOps space. This was attested to by some of the online platforms interviewed in their discussions with Ofcom.
Six workstreams cover the majority of UK agent engagements. Each is scoped as a discovery, designed as a target system, and delivered by senior UK engineers with an evaluation harness underneath it.
Scoped, designed and delivered by senior UK engineers. Framework-agnostic across LangChain, LangGraph, PydanticAI, CrewAI and native tool use. Model-agnostic across OpenAI, Anthropic, Google and open-weight models.
Two to four weeks that decide whether the workflow needs an agent, a deterministic pipeline or a classical model, and what the tool boundary and permission model look like if it does. Ends in a design you can put in front of your risk function, and a fixed price for the build. Duetto’s five-month evaluation of reinforcement learning for hotel pricing was this engagement: the question was whether the agent was worth building at all.
Agents that connect a language model to your APIs, databases, CRM, ERP and internal applications through validated, typed tool calls, with least-privilege access and an audit log of every action. Model Context Protocol servers, REST and gRPC wrappers, and identity wired into your existing provider, so the agent has exactly the permissions a new junior employee would.
Invoices, claims, applications, correspondence and case files: agents that extract, validate, self-correct and post into the system of record, with a human approval gate wherever money or personal data moves. Our open-source invoice-triage agent is the reference build. Where documents are the whole workload, this joins our AI document processing pipelines.
Retrieval-grounded agents that answer from your policies, contracts, records and regulatory guidance with source attribution, and that stay inside your data boundary. Chunking, embedding selection and retrieval evaluation measured separately from generation, so you can tell which half is failing. The Temple University assistant is the published example.
The workstream UK buyers skip most often, and the one the regulator asks about first. Task-level evaluation sets with real ground truth, regression tests across model versions, structured-output validation, bounded retries and adversarial testing. Without it a prompt change or a model upgrade is an unmeasured change to a production system.
End-to-end tracing, prompt and tool versioning, cost and latency budgets, drift alerts and incident response, on your AWS, Azure, GCP or on-prem Kubernetes. Extends our MLOps consulting and development practice into the operational record a UK auditor will want to read.
Agents pay back where skilled people currently read, check, route and act across several systems at volume, and where a wrong action has a cost that justifies measuring accuracy properly.
Complaint triage, customer assistance, collections journeys and credit-decision support under Consumer Duty and SM&CR. Our UK financial services work includes an FCA-regulated car-finance lender and a UK consumer lender whose reinforcement learning agent went live on customer traffic in 2023. See AI agents for financial services and our finance industry page.
Claims triage, first notice of loss, broker submissions and underwriting evidence, where the agent has to reason across a pack of attachments and post into the claims platform. Our MLOps work with Tractable, the UK insurtech, is the starting point.
Matter intake, contract review, clause extraction and research over privileged material, with source attribution and a human sign-off before anything leaves the firm. See our legal industry page.
Referral routing, clinical correspondence, prior authorisation and literature review under MHRA expectations, NHS data-flow rules and the ICO healthcare overlay. Human review is designed in from the first sketch. See AI agents for healthcare.
Correspondence handling, freedom of information requests and casework, with the Algorithmic Transparency Recording Standard record, G-Cloud-friendly contracting and UK sovereign cloud where required. We wrote Ofcom’s report on automated content classification.
Agent features inside your own product, built to survive real users. Evaluation, cost control and latency budgets from the start. We built Stable Audio for London-based Stability AI, a TIME Best Invention of 2023.
UK agent delivery sits inside a broader UK practice and a set of underlying service definitions.
The full methodology, framework and model choices, the live demo and the longer FAQ behind this page. See AI agent development services.
Retrieval, fine-tuning and LLMOps for UK buyers, where the agent is one workstream among several. See LLM consultancy UK.
The country-wide view across all of AI, including the regulator overlay, plus on-site delivery from our London AI consultancy page. See UK AI consulting.
Case study
Winder.AI helped Duetto evaluate offline reinforcement learning for dynamic hotel pricing. Over five months, the engagement progressed from behavioural cloning baselines through Implicit Q-Learning experiments on real booking data, revealing where RL outperforms simpler approaches, what data quality prerequisites exist, and how to evaluate pricing agents when ground truth is unavailable.
Case study
Winder.AI built a legal AI assistant for the Center for Public Health Law Research at Temple University, automating the scientific legal mapping work behind its MonQcle platform. In testing, the CPHLR team measured it as nearly 80% accurate at identifying the appropriate legal text for a coding question.
Case study
Our financial client is based in the UK. They specialise in providing services to the finance industry. Their data science team embarked on a project to leverage reinforcement learning within their product offering. Winder.AI, world-leading authors and experts on reinforcement learning, helped them deliver their POC into production. Read on to find out more.
Case study
Winder.AI helped CMPC, a large paper milling company, to optimise their production process by using reinforcement learning. CMPC are now able to automate industrial processes that were previously manual. This case study describes our approach and the results.
Common questions about hiring an AI agent development company in the UK. If your question is not covered here, book a call and we will answer it directly.
An AI agent development company builds software that uses a language model to plan a task, call your systems through tools, check its own results and act, and it ships that software into production with the controls a UK buyer has to show a regulator or an auditor. The work has four parts: deciding whether the workflow needs an agent at all (a deterministic pipeline or a classical machine learning model is often cheaper and easier to test), designing the tool boundary and the permission model, building the agent with an evaluation harness that measures it against ground truth, and running it in production with tracing, cost control and human approval gates. In the UK the same engagement usually carries FCA, ICO or MHRA expectations on top, plus the Algorithmic Transparency Recording Standard for central government work.
It depends on what you are buying, and the useful split is by provider type. Go to a global consultancy (Accenture, Deloitte) when agents are one workstream inside a multi-year transformation and the board wants that name on the contract. Go to a UK software house with an agent line (Geeks Ltd, Deployflow) when the agent is part of a wider software or DevOps programme. Go to a UK automation boutique (Openkit, Flux Technology) for a single back-office workflow at a fixed price, published at £10k to £30k per workflow in their FAQs as of 18 August 2026. Buy a platform (ServiceNow with Moveworks, Microsoft Copilot Studio) when the workflow already lives inside the vendor’s tool. Come to Winder.AI when the agent has to be measurably correct in production under UK regulation: autonomous systems in production since 2013, the O’Reilly book on reinforcement learning, a deployed assistant Temple University measured at nearly 80% accuracy, published GBP rates, and senior UK engineers led by Dr Phil Winder. Disclosure: this page is published by Winder.AI, and we are one of the options it compares.
We publish our rates. A scoping engagement that decides whether the workflow needs an agent, and designs it if so, runs two to four weeks for a fixed fee in the low five figures. A fixed-fee proof of concept covering one workflow, one system integration and an evaluation harness lands between £15k and £40k. Production builds and operations run on time and materials at £150 to £300 per hour, or £350 per hour for retained specialist consulting with a £5k monthly minimum. UK automation boutiques publish £10k to £30k per workflow (checked 18 August 2026); our proof-of-concept range starts higher because the harness that proves the agent works is inside it. See our pricing page for worked examples from real projects.
The UK has no single AI law, so the rules come from the sector regulator and from data protection. For financial services the FCA applies its existing framework to AI, so an agent that touches customers or credit decisions sits under Consumer Duty, the Senior Managers and Certification Regime and the operational resilience rules, and the firm has to be able to explain what the agent did and why. For personal data the UK GDPR governs, and the Data (Use and Access) Act 2025 loosened the rules on solely automated decisions provided the person is told, can contest the outcome and can get a human review. For clinical software the MHRA treats qualifying AI as a medical device. For central government the Algorithmic Transparency Recording Standard requires a published record of the tool. A UK group selling into the EU also inherits the EU AI Act, which our AI governance consulting practice covers.
Yes. We deploy open-weight models (Llama, Mistral, Qwen) on your own AWS, Azure, GCP or on-prem Kubernetes, including air-gapped environments, and we design the tool layer so that regulated data never leaves your boundary. Where a hosted frontier model from OpenAI, Anthropic or Google is the better engineering answer we say so, and we write down the data-residency and contractual consequences before you sign anything, so your legal team reads a design decision instead of discovering one after go-live.
It will, so the design assumes it. Every agent we ship has a typed output schema so a malformed answer is rejected before it reaches a system, validation on every tool call, bounded retries with a fallback to a safe behaviour, and a human approval gate in front of any action with money, personal data or legal effect behind it. Behind that sits an evaluation harness measured against real ground truth, so a prompt change or a model upgrade is tested before it ships. Our open-source invoice-triage agent shows the pattern end to end: 100% field-level extraction accuracy on its 20-invoice held-out set at a mean cost of $0.0081 per invoice.
You do. Our standard contract assigns the bespoke code, prompts, tool definitions, evaluation harness and configuration to you on payment. We keep ownership of our internal frameworks and patterns, and the agent itself is yours to run, change or hand to another supplier.
This page is the UK entry point: the regulator overlay, GBP pricing, UK clients and the UK delivery model. Our AI agent development services page carries the full methodology, the framework and model choices, the live demo and the longer FAQ. Same engineers and same engagement model. For language-model work more broadly, see our LLM consultancy UK page; for all of AI across the country, the UK AI consulting hub; and for on-site London delivery, AI consultancy London.
Typically two to four weeks from first call to kick-off. Discovery and scoping take one to two weeks and contracting another one to two. Urgent engagements have started inside a week. Our calendar generally fills four to eight weeks ahead, so get in touch early even if your timeline is flexible.
The team at Winder.AI are ready to collaborate with you on your AI project. We tailor our AI solutions to meet your unique needs, allowing you to focus on achieving your strategic objectives. Fill out the form below to get started.