Services · Mobile app development · AI apps
We take on AI app development Manchester organisations need when a model has to do real work: tagging hours of broadcast footage at MediaCityUK, turning a tenant's photo of damp into a repair job, or helping an online fashion brand answer shoppers at midnight. Codeeo plans the use case, prepares the data, builds the iOS, Android and web apps, and runs the model layer behind them under UK GDPR.
We have no Manchester office. Our team of 80+ sits across Dubai, Riyadh and Karachi and works remotely with clients in Manchester and Salford, running workshops, reviews and demos by video call with written notes after each one.
200+ companies servedFrom a first store to an ADX listed developer
What we build into Manchester AI apps
Manchester's economy mixes things that rarely share a postcode elsewhere: national broadcasters and production companies on the Salford Quays, some of the country's busiest online retailers, large social housing landlords, three big universities and a start up scene spread from the Northern Quarter to Ancoats. An AI feature that suits one of these makes little sense for another.
So we do not start from a list of model types. We start from the task a person in your organisation repeats every day and ask whether a model can do part of it reliably. The capabilities below are the patterns that come up most in Greater Manchester discovery sessions, from Salford Quays to Stockport and Oldham. Each one keeps a person in control of the outcome, logs what the model did, and can be switched off without breaking the rest of the app.
Production teams upload rushes, interviews and archive clips from a phone or editing suite. Models transcribe speech, detect faces and scenes, and suggest metadata tags and timecodes, which a researcher accepts or corrects. Search across the archive then works on what was said and shown, not just the file name.
Editors find the clip they need without scrubbing through hours of footage.
Tenants photograph damp, leaks or broken fittings in a guided flow. A vision model suggests the defect type and severity, the app collects the details an inspector needs, and urgent cases are routed straight to a person. For social landlords this supports the response times Awaab's Law now sets for damp and mould.
Hazards are logged properly the first time and the clock is visible to everyone.
For Manchester's online fashion and lifestyle brands, an assistant that understands requests such as an outfit for a festival in Heaton Park, checks live stock and sizes, and builds a basket. Returns questions are answered from your actual policy, and checkout runs through Apple Pay, Google Pay or Klarna where you already offer them.
Shoppers find what they meant, not just what they typed.
Customers snap a screenshot or street photo and see similar items from your range. We train or tune similarity models on your own product images, keep results within stock you can ship, and let merchandisers pin or exclude lines during a campaign.
Inspiration from social media turns into a product page in one tap.
Universities and colleges in Manchester field the same questions every September about accommodation, timetables, fees processes and support services. An assistant answers from approved institutional content, hands sensitive topics such as wellbeing straight to trained staff, and shows the source page for every answer.
Support teams spend Freshers' week on the cases that need a person.
Surveyors, care workers and engineers travelling across the ten boroughs dictate notes between visits. The app turns speech into structured job records, fills forms, and flags missing details before the worker leaves site, even with a weak signal on the edge of the Pennines.
Paperwork is finished in the van, not at the kitchen table.
Merchandising teams launching hundreds of lines a week get draft titles, descriptions and attributes generated from images and supplier data, written in your brand voice and checked against banned claims before a person approves them for the site.
New ranges go live faster with consistent copy.
Apps with comments, reviews or user uploads need moderation that fits the Online Safety Act duties Ofcom enforces. We combine automated screening with human review queues, user reporting and clear records of what was removed and why.
Communities stay usable and decisions can be explained.
A console showing accuracy on your test sets, live usage, cost per task and flagged outputs, so your Manchester product team can approve new prompts or models with evidence and roll back quickly if a release behaves badly.
Model updates become routine releases rather than leaps of faith.
Warehouses near Trafford Park and Manchester Airport, and venues busy on match days and concert nights, need rotas that follow demand. We build forecasting models from your order history, events calendar and weather, and show managers a suggested rota in the app that they can adjust before publishing it to staff phones.
Fewer shifts are over or under staffed on the city's busiest days.
Who this is for
Greater Manchester has its own combined authority, its own mayor and, through the Bee Network, its own integrated transport brand, and organisations here often work closely with that public sector ecosystem. That shapes procurement, data sharing and the standard of evidence buyers expect. These four situations are where our way of working tends to help most. Each starts with a short discovery to prove that a model can do the job on your own data before you commit to a full build.
Producers and post production houses on the Quays deal with large volumes of video and strict rights rules. Custom AI app development Manchester media teams ask for usually centres on search, logging and compliance checks rather than generating content. We keep rights metadata attached to every clip, respect editorial guidelines on synthetic media, and run processing in cloud regions that match your contracts with commissioners. Access controls follow production roles, so a freelancer sees only the programmes they are booked on.
We never train on your footage without written agreement.
Greater Manchester has some of the largest social housing providers in England, and Awaab's Law, named after a child who died in Rochdale, has made response times to hazards a legal duty. We build tenant reporting and inspector apps that capture evidence, triage with a vision model, track deadlines and keep the record a regulator or ombudsman will ask for. Tenants who prefer to phone are never forced into the app.
The region is home to many ecommerce businesses selling across the UK and abroad. For them, AI mobile app development Manchester style means conversational search, visual discovery and personalised offers that respect PECR consent for marketing. We connect to your ecommerce platform, stock feeds and customer data, and measure whether each AI feature actually changes conversion before expanding it.
Every AI feature ships behind a switch so you can A/B test it.
The University of Manchester, Manchester Metropolitan and Salford produce research teams and spin outs that have a model but need a product around it. We turn notebooks and research code into a secure app with sign in, billing, permissions and monitoring, so the founders can show investors and early customers something that works outside the lab. We can also prepare the product evidence that grant funders and accelerators in the North West tend to ask for.
Research IP stays with you and your institution.
How we work together
Smaller Manchester teams usually begin with a paid discovery and prototype, then commission a fixed scope first release. Organisations with ongoing model work, such as retailers adding features every season or landlords extending reporting to new hazard types, tend to move to a monthly retainer. Firms that want engineers embedded in their own stand ups can take a dedicated team. If you are comparing an AI app development company Manchester based against a remote partner, we are open about what remote delivery means: no site visits, but recorded sessions, fast written answers and full access to our tickets and code. Whichever option you choose, a named product lead stays your single point of contact from discovery through to the releases that follow launch.
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
Swift, Kotlin or cross platform frameworks for the apps; hosted language and vision models or open weight models in your cloud; vector search, queues and storage chosen to fit your data, budget and IT policies.
01Mobile
02Data and cloud
03Marketing and tracking
It depends mostly on data readiness and how many systems the app must connect to.
The fastest projects have clean data and one clear task, such as tagging product images. Slower ones involve legacy housing management systems, rights databases or several departments signing off. We set timing after the data check and the prototype, because until then nobody knows how much preparation the data needs. The agreed plan names each release and what it includes, and we report against it at every demo. If a deadline is fixed, such as a new season launch or a regulatory date, we say early which features fit before it and which should follow.
Schedule a free consultation and get a written recommendation, with costs, before you commit to anything.
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