Services · Mobile app development · AI apps
Codeeo handles AI app development for London businesses that need language models, document intelligence and prediction inside a product their customers and staff actually use. We design and build the mobile app, the web console and the model layer behind them, with UK GDPR, FCA expectations and an audit trail planned from the first sprint rather than added after a compliance review.
Our team of 80+ works across Dubai, Riyadh and Karachi and works remotely with London clients. Discovery, design reviews and demos run by video call, so your product owner, your compliance lead and our engineers see the same screen at the same time.
200+ companies servedFrom a first store to an ADX listed developer
What a London AI app can do
London buyers rarely ask for a chatbot for its own sake. A wealth manager in Mayfair wants adviser notes drafted from a meeting recording. An underwriter near the Lloyd's building wants a broker submission read and summarised before lunch. A West End retailer wants product questions answered in the shopper's own language. Each of these needs a model, but each also needs permissions, logging and a fallback to a human.
London also brings practical constraints: staff move between offices, client sites and home, customers expect instant answers in many languages, and procurement teams ask about data location early. The capabilities below are the ones London clients most often bring to discovery. We combine them according to who your users are, what data you hold and which regulator reads your files. Nothing here is a packaged product: every model call sits behind your own business rules, and every answer that matters can be traced back to its source.
An assistant inside your staff app that drafts client notes, suitability summaries or research digests from your own approved material. It cites the paragraph it used, flags gaps instead of guessing, and stores the draft for a human to approve before anything reaches a client, which suits firms working under the FCA Consumer Duty.
Analysts spend their time checking drafts rather than typing them.
Brokers, insurers and London law firms receive long PDFs in inconsistent formats. We build extraction pipelines that pull parties, limits, dates, exclusions and clauses into structured fields, then show a reviewer the original text side by side so every value can be confirmed or corrected with a tap.
Submissions are triaged in minutes and nothing is accepted unchecked.
Policy manuals, precedent banks, product sheets and internal wikis indexed so staff can ask questions in plain English. Access respects existing permissions, so a trainee in one practice group never retrieves material from a matter they are walled off from, and every answer links to the documents behind it.
Staff find the right answer without asking three colleagues.
London shoppers, patients and tenants speak hundreds of languages at home. We add translation and multilingual answering to customer apps, with English kept as the record language for complaints and regulated communications, and clear handover to a person whenever the assistant is unsure.
More customers get help in the language they think in.
Models that score payments, claims or account changes for unusual patterns and surface the reasons alongside the score. Investigators see why an item was flagged, can dismiss it with a note, and that feedback goes back into the next round of model tuning.
Fewer false alarms reach the investigations team.
Recording, transcription and structured summaries for client meetings, with consent prompts built into the flow and retention periods you set. Summaries map to your CRM fields so actions and follow ups land where the team already works.
Every client meeting leaves a usable record within the hour.
Where an app makes or supports a decision that affects someone, such as a credit limit or a claim route, we design screens that explain the main factors in plain language and give the person a way to ask for human review, in line with UK GDPR rules on automated decisions.
Customers understand outcomes and complaints fall.
A web console where your team runs test sets against each new prompt or model version, compares accuracy and tone, and watches live usage for drift, cost spikes or unsafe outputs before a London client notices anything has changed.
Model changes ship with evidence, not hope.
Biometric sign in, device binding, short session lifetimes and remote wipe for staff apps that carry confidential material on the Tube or in client offices. Sensitive prompts and responses stay out of device logs and crash reports.
A lost phone is an inconvenience, not a breach.
Staff and customers open apps between Underground stations and on patchy rail signal. We cache recent answers, queue questions and documents while offline, and sync safely once the connection returns, so AI mobile app development London users actually rely on survives the Elizabeth line as well as the office Wi-Fi.
The app stays useful between Zone 1 and Zone 6.
Who this is for
London has more regulated firms, more in house legal teams and more multilingual customers than anywhere else in the country, and that mix shapes how an AI app should behave. Buyers here also tend to have seen several demos already, so they want proof on their own data rather than a polished pitch. The situations below are the ones where our approach fits best. If yours is different, discovery will tell us both quickly whether a custom build makes sense or whether a licensed tool would serve you better.
Banks, payment firms, asset managers and brokers need AI that the second line can test and the board can explain. We plan model governance with your risk team: documented purposes, human approval points, logs that support a Consumer Duty review, and a clear record of which model version produced which output. If you plan to use the FCA's AI Lab or its testing services, we can prepare the product and its evidence for that conversation.
Your compliance team joins discovery, not the final week.
Firms around Holborn, Chancery Lane and the Lloyd's market spend hours reading. We build document intelligence into a mobile and web tool so fee earners and underwriters review extracted points rather than raw pages. Confidentiality comes first: client matter walls, no training on your data by third party model providers, and UK or EU hosting where your clients require it. Time recording and matter codes can be attached to each review so the hours spent checking extracted points are billed correctly.
Solicitors keep their SRA duties; the app supports them.
Retailers with flagship stores and big online audiences want product discovery that understands vague requests, such as a gift for a runner or a dress for a summer wedding. We connect recommendation and search models to your catalogue, stock and returns data, and pay through Apple Pay, Google Pay or Open Banking checkouts already familiar to London shoppers. Store staff get the same assistant on a handheld, so the answer a shopper sees online matches the one given on the shop floor.
London has a dense network of NHS trusts, private clinics and digital health start ups. For triage helpers, clinical note tools or patient education apps we plan around the NHS Digital Technology Assessment Criteria, clinical safety standards and the MHRA position on software as a medical device, and we keep the model in a supporting role unless your clinical safety case says otherwise.
Clinical claims are scoped carefully with your clinical lead.
How we work together
Most London clients start with a fixed scope first release covering one high value use case, then move to a monthly retainer for new features, model updates and evaluation runs. Firms with a longer roadmap sometimes take a dedicated squad of engineers and a product lead who work inside their sprint rhythm and tooling. All three run remotely, with written decisions after every call so your internal audit trail stays complete. Choosing an AI app development company London stakeholders can audit matters as much as choosing the model, so every engagement includes shared access to tickets, test results and release notes.
A defined build with a deadline
We agree what the product has to do, write it down with a price and a date, and build exactly that. Changes are priced before they are made, not discovered on the invoice.
A product that keeps evolving
Named engineers who work your hours, join your standups and stay on the codebase. You direct the backlog; we own the quality of what ships.
Something live that needs looking after
A monthly block of hours for improvements, fixes and the small requests that otherwise wait months. Unused hours carry for a quarter.
Technology
We work with hosted models from the major providers, open weight models you can run in your own cloud, vector databases, and native or cross platform mobile code. The choice follows your data residency, cost and vendor risk rules.
01Mobile
02Data and cloud
03Marketing and tracking
Use case selection, data preparation, model integration, the app itself and monitoring after launch.
A London project normally starts with one painful process, such as reading broker submissions or answering repeat customer questions. We confirm the data exists and can be used lawfully, build a prototype, measure it against your own examples, then wrap it in a mobile or web app with permissions and logging. After release we watch performance, cost and safety, and ship improvements as tested updates rather than silent changes. Custom AI app development London firms commission usually follows this order because it proves value on one process before money goes into the next.
Schedule a free consultation and get a written recommendation, with costs, before you commit to anything.
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