Mobile AI apps

Mobile application development with artificial intelligence

A mobile app with artificial intelligence uses the camera, voice, the user's context and the app's data to offer smart search, personalisation, assistants or image recognition. Depending on the case, the model runs on the device itself (fast and private) or in the cloud (more powerful); we design the right architecture for your product.

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By Oliver Guirado · Updated on October 28, 2026 · 5 min read

What AI can do in a mobile app

Smart search

The user types or says what they are looking for in their own words and the app understands the intent, not just matching keywords.

Personalisation

Screens, content and offers that adapt to each person's behaviour and context.

Camera and vision

Document scanning, product or part recognition and reading data from a photo.

Voice

Dictation, voice commands and spoken answers in the app.

Security and anti-fraud

Detection of anomalous behaviour and identity verification, with human control.

Built-in assistant

A copilot that answers questions and carries out actions inside the app.

AI chatbots →

If you are after the complete product with strategy, UX and backend, see custom AI app development.

AI on the device or in the cloud

Criterion	On the device	In the cloud
Latency	Very low, works offline	Depends on the network
Privacy	Data does not leave the phone	Requires sending data and agreements with the provider
Model power	Limited by the hardware	Far more capable models
Usage cost	No cost per query	Pay per use
Updates	With the app or a model download	Immediate, without touching the app
Examples	Image recognition, simple voice, edge detection	Conversational assistants, summaries, complex searches

Many apps combine both: fast, private tasks on the device and complex reasoning in the cloud. We choose according to latency, privacy, cost and required quality.

Sample mobile AI app projects

Sample project · Fintech

Neighbourhood banking app with an assistant and document scanning

Problem

Users abandoned sign-up because of the number of documents and forms, and support received the same queries again and again.

Solution

An app with camera document scanning and data extraction, real-time validation and an assistant that answers questions about the process in a clear tone, handing over to an adviser when appropriate.

Steps

Map of the sign-up process and of the drop-off points.
Document scanning and extraction with validations.
Assistant with a regulated knowledge base and scope limits.
Security and privacy tests.
Phased launch with funnel measurement.

Target outcome

A smoother sign-up, fewer repetitive queries and traceability of every step. More in fintech apps.

Technology

Cross-platform app, on-device OCR, secure backend, language model with EU data.

Sample project · Events and entertainment

Leisure app with personalised recommendations and natural-language search

Problem

The range of events was huge and users did not find plans that matched their tastes; generic notifications were ignored.

Solution

Natural-language search ("a quiet plan with live music this Saturday"), recommendations based on history and location, and personalised alerts.

Steps

Analysis of usage data and design of the discovery experience.
Semantic search over the event catalogue.
Recommendation engine and notification rules.
A/B tests and tuning.

Target outcome

More event discovery and more relevant notifications. More in event apps.

Technology

Mobile app, semantic search, recommendation engine, segmented push notifications.

The projects on this page are illustrative, anonymised examples of how we approach this kind of work. Every real project is defined with your information, your systems and your goals.

How we develop it

Use case and data: which AI feature adds value and what information the app has.
Experience design: how the AI is presented to the user, what they control and how errors are corrected.
Architecture: model on the device, in the cloud or hybrid; security and cost per use.
Native or cross-platform development: iOS, Android, Flutter or React Native.
Evaluation and launch: AI quality tests, publication in the stores and continuous improvement.

More information about our general mobile application development service.

Privacy, performance and store publication

Privacy: tell the user which data is used, request camera, microphone or location permissions only when needed and comply with GDPR.
Performance and battery: optimise models, use device acceleration and avoid unnecessary calls.
Store policies: declare the use of AI and data according to Apple and Google rules.
Transparency: indicate when the user is interacting with an AI system and offer a human alternative.

Reference prices

Scope	Indicative investment
AI feature added to an existing mobile app	€8,000 – €30,000
Mobile app MVP with AI as the core feature	€25,000 – €60,000
Full iOS and Android app with several AI features	€60,000 – €180,000

Indicative reference prices in euros, excluding VAT, for projects in Spain and Europe in 2026. The final amount depends on scope, integrations and data quality; we confirm it with a fixed quote after a first meeting.

Frequently asked questions

What is a mobile app with artificial intelligence?

It is an application that uses AI to understand language, images, voice or data and offer features such as smart search, personalisation, assistants or image recognition.

Can AI run on the phone itself?

Yes, for tasks such as image recognition or simple voice. Complex tasks, such as conversational assistants, usually need the cloud. Many apps combine both options.

How much does a mobile app with AI cost?

Adding an AI feature to an existing app costs between €8,000 and €30,000; an MVP with AI as the core feature, between €25,000 and €60,000; and a full iOS and Android app, between €60,000 and €180,000.

What privacy requirements must be met?

GDPR, clear information to the user, permissions only when needed, contracts with the AI providers and the data-use declaration in the app stores.

Does it work offline?

The features that run on the device do. Those that depend on cloud models require a connection; a fallback behaviour without a network can be designed.

Shall we talk about your project?

Tell us about your case and we will reply within 24-48 hours with a proposed scope and an indicative quote.

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Tell us about your project

Describe what you want to achieve and which systems you work with. We reply within 24-48 hours.

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Artificial intelligence services and guides

Everything we do with AI for business, from the diagnostic to the product in production. Artificial intelligence for business.