To add AI to an existing mobile app, start with one task your users already need to complete. Define the input, the output they can use, and the point where a person should review or approve the result. Then assess the app’s interface, backend, data access and release process together.
An assistant that explains a record, a tool that drafts a document, and a feature that acts on an account are different projects. A useful brief describes the work the feature will do and the boundaries it must respect. That gives a software development team something concrete to estimate and test.
Choose a first feature with a complete user journey
Describe the moment of use. A person opens a record, asks a question, waits for a result, reviews it and decides what to do next. Identify which part is slow or difficult today. The first release should improve that journey with an output the user can inspect.
For example, a draft-writing feature might prepare text for approval. A catalogue assistant might help narrow a search. A document feature might organise information for review. Choose a bounded task before combining several tools or allowing the system to take actions automatically.
Review the existing app and the data it uses
Bring the application’s user roles, relevant screens, available APIs and data sources into discovery. Clarify what the feature may read, what it may store and whether it can change anything. The new feature should follow the access rules of the existing product.
Some tasks can start with information the user provides directly. Others need a connected knowledge source or an application record. Agree who owns each source and how access changes are handled. A first technical proof should test the hardest connection before the wider feature depends on it.
Design the waiting, review and recovery states
The mobile interface needs to explain what is happening while work is in progress. Plan the input screen, progress state, result view and next action together. Users should know which content is generated and have a practical way to correct, retry or dismiss it.
Include interrupted connections, rejected permissions, unavailable services and incomplete responses in the review plan. If a person leaves the screen, decide whether the work continues and where its status appears later. These are product decisions that affect both the mobile app and the backend.
Evaluate the task before choosing the larger rollout
Build a set of representative examples with expected behaviour. Include ordinary requests, ambiguous inputs and situations where the feature should ask a follow-up question. Review output quality, response time and usage cost together. A general model score does not establish whether this particular feature works for your users.
For a feature that changes business information, decide which actions need human approval and how completed actions are recorded. Keep the first release small enough to inspect. Model choice, retrieval, hosting and any additional training should follow the task and data requirements.
Agree ownership, operating cost and the release boundary
The proposal should state the feature scope, supported platforms, integrations and acceptance criteria. Separate the implementation estimate from ongoing provider, hosting and support costs. Record assumptions about usage so the operating model can be revisited when real demand is measured.
Decide who owns source code, service accounts, configuration, evaluation examples and release documentation. Identify the team responsible for monitoring and for updating the feature when the app or its dependencies change. A first release is easier to maintain when those responsibilities are explicit.
Use the Brainbaby portfolio to make the discussion concrete
Brainbaby AI brings conversations, media, documents and presentations into a shared workspace. Its owned-product case study gives you interfaces and workflows to examine. Baby Astro offers another example of specialised information presented through a consumer mobile experience.
For your project, send us the existing app, the task you want to improve, the relevant data sources and the first-release constraints. We can discuss discovery, a bounded integration proof or a defined implementation. The service overview is available in English, Turkish, German, French, Spanish, Italian, Portuguese, Dutch, Arabic and Polish.