AI apps

AI App Development

AI app development means building web and mobile apps in which AI performs a core function: voice dialogue, image analysis, recommendations or intelligent search. Context Studios builds such apps as progressive web apps, native iOS or Android apps or cross-platform solutions – from prototype to store launch, with a GDPR-compliant architecture.

Glass pavilion with a curved steel-and-glass roof photographed from below, one glass panel tinted tealAI-generated image
Native & cross-platformAI-powered UXApp store readyOffline-capable
  1. Workshop
  2. Setup
  3. Sprint
  4. Build & Support

Fixed price after scoping · proposal within 48 h

Last updated:

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What is AI app development?

AI service

AI app development covers the design and implementation of mobile and web-based applications that use artificial intelligence as a central function. Unlike traditional app development, AI models are integrated directly into the architecture – on the server side via APIs such as Claude or GPT, or on the client side with compact on-device models.

Specialisation
AI-powered web and mobile apps, PWAs, cross-platform
Technologies
Next.js, React Native, Claude API, TensorFlow Lite, Core ML
Target group
B2B SaaS, B2C platforms, enterprise applications
Typical project duration
Typically 4–14 weeks depending on platform and feature scope
Compliance
GDPR, app store guidelines, accessibility (WCAG)

AI software developmentAI product developmentAI SaaS developmentChatbot developmentAI assistant development

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Which AI features can your app get?

What sets our AI apps apart

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Cross-platform AI integration

One codebase, all platforms: our AI apps run as a PWA in the browser, as an installable desktop app and on mobile devices. The AI logic is implemented once and works everywhere – with platform-specific optimisations for the best possible performance on every device.

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Real-time AI streaming

Users expect instant reactions. Our apps use streaming responses from AI models to display results in real time – token by token, like a real conversation partner. This noticeably shortens perceived waiting time and creates a natural interaction experience.

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Offline-capable AI features

Not every AI function needs an internet connection. We integrate compact ML models directly into the app that also work offline – for image classification, text recognition or speech processing. More complex tasks are handed over seamlessly to cloud APIs as soon as a connection is available.

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Computer vision integration

Camera-based AI features for your app: document recognition, product identification or augmented reality. Our computer vision integration uses the device camera for real-time analysis and shows results directly in the app interface.

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Natural language interaction

From chatbots and voice control to intelligent text analysis: our apps understand natural language in German, English, French and Italian. Integrating Claude and GPT enables context-aware conversations that feel like talking to an expert.

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AI-powered analytics

On request, we deliver AI apps with intelligent analytics: user behaviour analysis, automatic anomaly detection and predictive metrics. You don't just see what users do – you get indications of what they might do next and how you can improve the experience.

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How does an idea become a market-ready AI app?

  1. (01)

    Consultation call

    Free initial call via video. We get to know your business, identify AI potential and give you a first assessment of feasibility and schedule.

    Day 1
  2. (02)

    Proposal & planning

    You receive a written proposal with scope, schedule and fixed price.

    Days 2–3
  3. (03)

    AI-accelerated development

    Agile development with weekly demos. Goal: a working MVP in about 4 weeks, with production-ready code and automated tests.

    Weeks 1–4
  4. (04)

    Launch & support

    Production deployment with complete documentation.

    Week 4+

Questions about AI app development

(01)Progressive web app or native app – what do you recommend?
For most AI applications we recommend progressive web apps (PWAs) built with Next.js: they run on all devices, can be installed and don't need an app store review process. Native apps make sense if you need hardware access (for example the camera for computer vision) or the highest possible performance. We advise you transparently on the best strategy.
(02)Can AI run directly on the device, without the cloud?
Yes, with on-device ML models. TensorFlow Lite and Core ML make it possible to run compact AI models directly on the smartphone – ideal for image classification, text recognition or simple NLP tasks. More complex tasks such as longer text generation or in-depth analysis still require cloud APIs such as Claude or GPT.
(03)How do you integrate AI streaming into mobile apps?
We use server-sent events (SSE) and WebSocket connections for real-time streaming of AI responses. The Vercel AI SDK abstracts the complexity and delivers token-by-token streaming with careful battery usage on mobile devices. The result is a natural, chat-like experience without noticeable waiting, even for longer answers.
(04)What does developing an AI app cost?
Costs depend on the platform (PWA, native or cross-platform), feature scope and AI integration. Fixed price after scoping, proposal within 48 hours. A good starting point is a Prototyping Sprint (2 days) at a fixed price of €4,500, in which we test your app idea with a clickable prototype and real AI functions.
(05)How fast can AI features in the app respond?
With streaming, intelligent prefetching, caching of frequent requests and optimised prompt design, we keep latency low; on-device models usually respond particularly fast. Streaming responses ensure that users get visual feedback immediately, and loading states make longer analyses understandable for users.
(06)Can you add AI features to an existing app?
Yes, we extend existing apps with AI functionality without completely rewriting the existing codebase. Through API integrations and modular components we add AI features such as intelligent search, chatbots or recommendation systems. The integration happens step by step and is tested at every stage.
(07)How do you ensure good app performance with AI?
AI models can increase response times. We counter this with several strategies: lazy loading of AI features, background processing for time-consuming analyses, optimised model choice (smaller models for simple tasks), edge computing for low latency and intelligent caching. The result: AI features that make the app feel faster, not slower.
(08)Do you also support app store submission?
Yes, we handle the entire app store submission process: creating store listings, screenshots and descriptions, complying with Apple and Google review guidelines (especially for AI features), and communicating with the review teams if questions arise. For enterprise customers we also set up MDM deployment.
(09)How is user data protected in the AI app?
Data protection is a core part of our app architecture: end-to-end encryption for sensitive data, local processing where possible, anonymised analytics and transparent consent. We choose API terms under which your data is not used for model training. Data is stored on European servers and processed in line with the GDPR.
(10)Do you also offer app updates and maintenance after launch?
Yes. We fix defects free of charge for 30 days from final delivery. After that we offer maintenance by agreement: regular updates for operating system compatibility and frameworks, AI model updates, bug fixes and new features. Fixed update cycles, for example monthly, have proven effective for keeping the app up to date and performing well.
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Technologies for AI apps

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AI & ML

Anthropic ClaudeOpenAI GPTGoogle GeminiOpen-Source LLMs (Llama, Qwen, DeepSeek, Mistral)ConvexRAG & Vector DBs (Pinecone, Weaviate)MCP (Model Context Protocol)Hugging Face TransformersComputer Vision (YOLO, SAM)ElevenLabs (Voice AI)Google Veo (Video AI)
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Web & Mobile

Next.js & ReactTypeScriptReact Native & ExpoTailwind CSSShadcn/uiVercel Edge Runtime
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Backend & Data

Node.js & Hono (Edge)PythonPostgreSQL & SupabaseConvex (Real-Time DB)RedistRPC & GraphQLOpenAPI
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DevOps & Infrastructure

Vercel & AWSDocker & KubernetesCI/CD-Pipelines (GitHub Actions)OpenTelemetry & GrafanaLangfuse (LLM Monitoring)
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Which industries do we build AI apps for?

Health & wellness

AI apps for symptom tracking, personalised health recommendations and medication reminders. Health apps can use AI for predictive health analyses and connect securely to wearables – GDPR-compliant and observing the MDR where it applies.

Hospitality & food

Intelligent ordering apps with AI-based menu recommendations, automatic allergen detection and personalised nutrition suggestions. Our food apps analyse preferences, intolerances and trends to create individual experiences.

Mobility & transport

AI-powered apps for route optimisation, fleet management and ride sharing with intelligent demand forecasting. Mobility apps combine real-time GPS data with predictive models for good utilisation and short waiting times.

Education & learning

Adaptive learning apps that adjust to the individual level, analyse progress and generate personalised exercises. AI tutors answer questions in natural language and explain complex concepts at the right level of understanding.

Trades & facility management

Field service apps with AI damage detection via camera, automated job logging and intelligent dispatch planning. Our apps also work offline on construction sites and synchronise data automatically when a connection is available.

Sport & fitness

AI-powered training apps with motion analysis via computer vision, personalised training plans and real-time form correction. Our fitness apps motivate users with data-based progress analyses and intelligent periodisation.

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Example projects

Examples we can build for you

Customer service

AI-powered support agent

An AI agent that understands customer requests in natural language, accesses internal knowledge bases and delivers answers automatically – around the clock.

Automated first response · Multilingual · Available 24/7
Knowledge management

RAG-based document system

An intelligent knowledge system with RAG architecture: it searches large document collections and delivers source-based answers in seconds.

Source-based answers · Fast search · Scalable
Process automation

Workflow automation with AI agents

Autonomous AI agents that automate recurring business processes – from data extraction to reporting.

Automated end to end · Fewer errors · Time savings
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AI apps – consultation in Berlin

Founder AI-native since
2024
Email
info [at] contextstudios [dot] ai

Your AI app – designed and built in Berlin

From app idea to store launch: tell us about your vision and we'll show you what is possible with AI.