Chatbots are not AI apps. Real AI-native development means your app generates interfaces on demand, processes data on-device for privacy, and meets EU regulatory requirements by design. We build mobile applications where intelligence shapes every interaction, not just a chat window in the corner.
Adding a chat interface to your app is not AI-native development. It's a bolt-on. True AI integration means the intelligence shapes how your app looks, responds, and adapts. Users interact with dynamic interfaces generated in real-time based on their intent. Not another "wall of text" conversation.
This is the shift from conversational AI to Generative UI (GenUI). When a user asks to book a restaurant, they don't type back and forth negotiating times and party sizes. The app generates a booking form with date pickers, time sliders, and native controls. The AI decides what to show. Flutter renders it instantly. The user taps, swipes, and confirms.
We build these experiences using Google's A2UI protocol (Agent-to-User Interface) with Flutter. The combination delivers AI-driven interfaces that feel native because they are native. Your design system, your brand, your widgets. The AI orchestrates them.
70% of enterprise AI initiatives stall or fail. The pattern is consistent: teams bolt chatbot APIs onto existing apps, users get frustrated with endless text exchanges, and the project gets deprioritised. Chat is an inherently low-bandwidth medium for complex tasks. You cannot configure a dashboard, compare product options, or navigate a workflow efficiently through conversation.
The solution is not better prompts. It's better architecture. AI-native apps separate intent (what the user wants) from presentation (how it's shown). The AI handles reasoning. The client handles rendering. This creates a clear security boundary where prompt injection attacks cannot generate malicious code, because the AI can only request components you've pre-approved.
Cloud-dependent AI creates three vulnerabilities for your app: latency (users wait for round trips), cost (every inference hits your server bill), and privacy (sensitive data crosses network boundaries). Edge AI solves all three.
Google's Gemini Nano, running directly on mobile devices via the AI Edge SDK, enables offline-capable intelligence. Grammar correction, smart replies, local document summarisation, and UI component selection can happen without network connectivity. For healthcare apps handling patient data or finance apps processing sensitive transactions, on-device processing means the data never leaves the phone.
The business case is compelling. A hybrid architecture that routes simple tasks to the device and complex reasoning to the cloud reduces long-term AI costs by 30-50% compared to cloud-only approaches. Your users get faster responses. Your CFO sees lower OpEx. Your compliance team sleeps better.
As of February 2025, specific AI practices are illegal in the EU. Manipulative algorithms that exploit psychological vulnerabilities. Emotion recognition in workplaces or schools. Biometric categorisation inferring race, politics, or religion. If your app contains these features, you're already exposed.
By August 2026, high-risk AI systems (healthcare, education, employment, credit scoring) face strict compliance obligations under Articles 10 and 12 of the EU AI Act. This includes bias audits on training data, specific logging requirements capturing every inference with timestamps and input data, and transparency markers so users know they're interacting with AI.
We've studied the regulation in depth. Our blog post on the EU AI Act Guide for App Developers breaks down the requirements. When you build with us, compliance isn't a retrofit. It's built into the architecture from sprint one.
Most development agencies cannot offer this. They'll build your AI features and leave compliance to your legal team. We deliver both because separating engineering from regulatory requirements is how projects fail audits.
GenUI applications with Flutter and A2UI: Apps where AI generates contextually relevant interfaces in real-time. Restaurant finders that show booking forms. Travel apps that display comparison cards. Productivity tools that adapt their UI to the task at hand.
Edge AI mobile apps with Gemini Nano: Privacy-first applications that process sensitive data on-device. Health trackers analysing biometric data locally. Note-taking apps with private AI assistants. Field service tools that work offline in areas with poor connectivity.
Hybrid intelligence architectures: Systems that route workloads intelligently between cloud and edge. Simple tasks run locally for speed. Complex reasoning hits Vertex AI or GPT-4 when needed. Users get the best of both without managing the complexity.
EU AI Act compliant systems: High-risk AI applications built for regulatory approval. Compliance logging, bias audit infrastructure, and Article 50 transparency requirements baked into the codebase.
AI projects demand more upfront clarity than traditional app development. The interaction model, on-device vs cloud split, data governance, and compliance requirements must be defined before code is written. Retrofitting these decisions is expensive.
Discovery with The App Gameplan: In 4 weeks, we map your AI use cases, define the intelligence architecture, classify regulatory requirements, and deliver a fixed-price development quote. For AI projects, this step is non-negotiable. Skipping it leads to the 70% failure rate mentioned above.
Architecture design: We specify the component registry (which UI elements the AI can request), the routing logic (what runs locally vs cloud), and the compliance logging infrastructure. This blueprint governs every development decision.
Agile development: Two-week sprints with working demos. You see AI features functioning early, which exposes UX issues before they become expensive to fix. The AI's "personality" and response patterns emerge through iteration, not guesswork.
Compliance validation: For high-risk applications, we conduct bias audits on training data, verify logging captures required metadata, and ensure transparency markers are correctly implemented.
Enterprise teams modernising legacy apps: Your existing app works but feels dated. Users expect AI-powered experiences. You need a partner who understands how to integrate GenUI without rebuilding everything, while ensuring the new features pass IT security reviews.
Product teams building AI-first: You're creating a new product where intelligence is the core value proposition. Not an add-on. The entire UX should adapt to user intent. You need developers who've shipped this type of application before.
Regulated industries entering AI: Healthcare, fintech, HR tech, edtech. You see the opportunity but fear the compliance minefield. You need architecture that satisfies both innovation goals and regulatory requirements.
Scale-ups expanding to Europe: You're a US or UK business launching in EU markets. Your AI features must comply with regulations that don't exist in your home market. You need an audit of current practices and a remediation roadmap.
AI projects fail when teams rush to implementation without answering fundamental questions. What's the intelligence architecture? What runs on-device? How do we handle EU compliance? What's the actual cost of cloud inference at scale?
The App Gameplan answers these questions in 4 weeks for £3,500. You receive an AI capability assessment, architecture blueprint, compliance gap analysis (if applicable), and a fixed-price development quote. The fee is credited against development if you proceed.
For AI app development, starting with The Gameplan isn't optional. It's how successful projects begin.
An actionable four-week plan with clear deliverables and an unbeatable £3,500 price point, credited against your first development sprint.
Total client time commitment: 5-7 hours across 4 weeks
We meet with your key stakeholders to understand your business goals, user needs, and technical constraints. You'll share any existing research, designs, or documentation you have.
Our engineering team assesses the technical feasibility, identifies integration points with your existing systems, and evaluates architecture options.
We determine whether Flutter, native development, or another approach makes the most sense for your specific requirements.
We create clickable prototypes so you can experience your app before it's built. You'll test navigation flows, validate the user experience, and gather feedback from stakeholders.
Alongside this, we prioritise features based on business value and technical complexity, mapping out a phased delivery plan with a detailed cost estimate.
You receive your complete Gameplan pack, plus a presentation walkthrough with Q&A. Your team walks away with everything needed to make a confident decision.
Why UK businesses choose Foresight Mobile for AI app development
AI app development requires close collaboration during discovery and iteration phases. Working with a Manchester-based team means real-time communication, face-to-face workshops when needed, and developers who understand UK and EU regulatory contexts. No timezone delays when you're debugging model behaviour or adjusting AI responses.
Our team has implemented GenUI with Flutter since the A2UI standard launched. We've shipped edge AI features using Gemini Nano. We've studied the EU AI Act requirements in depth.
Manchester HQ • Same Timezone • Regulatory Knowledge • Proven AI Experience
Prompt injection is the biggest AI security threat. Attackers trick models into generating malicious outputs. Our GenUI architecture neutralises this risk. The AI sends declarative data (JSON), not executable code. Your app maintains a component registry of pre-approved widgets. If the AI requests something not in the registry, it's ignored.
CISOs can approve AI features knowing they cannot be weaponised. The AI rearranges your Lego blocks. It cannot create new ones.
Component Registry • No Code Execution • Prompt Injection Protection • CISO-Approved
Not everything needs GPT-4. A smart routing system sends simple tasks to Gemini Nano on-device and complex reasoning to Vertex AI in the cloud. Users get the right intelligence for the job without managing the complexity.
Research shows this approach reduces AI operational costs by 30-50% compared to cloud-only architectures while improving response times for common operations.
Intelligent Routing • 30-50% Cost Reduction • Optimal Performance • Privacy Control
Compliance is not a legal afterthought. It's an engineering requirement. We build high-risk AI systems with Article 10 data governance, Article 12 compliance logging, and Article 50 transparency markers from the start. Bias audits on training data. Inference logs capturing timestamps and inputs. Clear AI disclosure to users.
For US and UK companies entering EU markets, we provide gap analysis and remediation roadmaps to bring existing AI features into compliance.
Article 10 Data Governance • Article 12 Logging • Bias Audits • Transparency
Sensitive data should never leave the device. With Google's Gemini Nano via the AI Edge SDK, your app processes information locally on the neural processing unit. Healthcare apps analyse biometrics privately. Finance apps handle transactions without cloud exposure. Field service apps work completely offline.
The result: instant responses with zero latency, no per-inference cloud costs, and inherent GDPR compliance through data minimisation.
Gemini Nano • AI Edge SDK • Offline Capability • Zero Latency
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We build apps where AI generates the interface, not just the responses. Using Google's A2UI protocol with Flutter, your app creates contextual UI components in real-time. Users book reservations with sliders and date pickers instead of typing back and forth. They compare options with cards and filters, not endless chat.
The AI decides what to show. Flutter renders it instantly with your design system. Native performance, your brand, intelligent orchestration.
A2UI Protocol • Flutter GenUI SDK • Native Widgets • Brand Consistency
Healthcare: On-device processing for patient data privacy, AI-assisted diagnostics with compliance logging, field tools that work offline. Finance: Private transaction analysis, fraud detection at the edge, regulatory-compliant AI decisioning. Education: Personalised learning experiences, accessibility features, classroom tools meeting EU AI Act requirements.
Retail and hospitality: GenUI for booking and purchasing workflows, personalised recommendations. Field service: Offline-capable AI assistants, real-time decision support. Any industry with complex workflows, privacy requirements, or EU market exposure benefits from AI-native architecture.
Yes. For existing AI applications, we provide a Prohibited Practice Scan identifying features that became illegal in February 2025, a High-Risk Classification Report determining whether your app falls under strict compliance requirements, and a Gap Analysis for August 2026 obligations.
For new development, we build compliance into the architecture from sprint one: Article 10 data governance with bias audit infrastructure, Article 12 compliance logging capturing required metadata, and Article 50 transparency requirements including AI disclosure and content watermarking where applicable.
Prompt injection is the primary AI security threat: attackers craft inputs that trick models into generating malicious outputs. Our GenUI architecture addresses this through client sovereignty. The AI sends declarative JSON describing UI components, never executable code.
The client app maintains a component registry of pre-approved widgets. If the AI requests a component not in the registry, it's ignored or replaced with a fallback. This means the AI can only rearrange pre-built blocks. It cannot invent new functionality or execute arbitrary code, neutralising prompt injection attacks.
On-device models like Gemini Nano are smaller than cloud models like GPT-4 or Gemini Pro. They excel at specific tasks: grammar correction, smart reply generation, local document summarisation, intent classification, and UI component selection. They're not suited for complex multi-step reasoning or tasks requiring broad world knowledge.
This is why we architect hybrid systems. Simple, frequent tasks route to the device for speed and privacy. Complex reasoning routes to the cloud. The user experience combines the strengths of both without managing the complexity.
Chatbots are text-in, text-out interfaces. Users type questions, the AI responds with paragraphs. This works for simple queries but fails for complex tasks. You cannot efficiently book flights, configure dashboards, or compare products through conversation. Users experience "chat fatigue" and abandon the interaction.
AI-native apps use GenUI to generate appropriate interfaces for each task. Booking a table? The AI generates a date picker and time selector. Comparing laptops? A comparison table appears. The AI chooses the best UI pattern for the task. Users interact through taps, swipes, and familiar controls rather than typing.
AI projects require longer discovery phases than traditional app development. Architecture decisions around AI routing, on-device capabilities, model selection, and compliance requirements must be resolved before code is written. Retrofitting these decisions is expensive.
After a 4-week App Gameplan, typical timelines are: GenUI feature integration 12-16 weeks, edge AI implementation 14-20 weeks, comprehensive AI-native application with compliance 6-12 months. Complex enterprise integrations with multiple AI agents can extend beyond 12 months.
AI app development costs vary based on the scope of AI integration. GenUI features added to an existing app might cost £40,000-80,000. A greenfield AI-native application with edge AI, hybrid architecture, and EU AI Act compliance typically ranges from £80,000-150,000.
The variables include: number of AI use cases, on-device vs cloud processing split, regulatory classification (high-risk AI requires more compliance infrastructure), and whether you're building new or integrating with existing systems. The App Gameplan provides a detailed, accurate quote after 4 weeks of discovery for £3,500.
The EU AI Act is comprehensive artificial intelligence regulation affecting any company offering AI systems in European markets. This includes US and UK companies whose apps are available in European app stores. The Act categorises AI systems by risk level and imposes corresponding obligations.
As of February 2025, certain AI practices are prohibited (manipulative algorithms, workplace emotion recognition, biometric categorisation). By August 2026, high-risk AI systems in healthcare, education, employment, and credit scoring must implement specific compliance measures. Our EU AI Act Guide for App Developers covers the details.
On-device AI runs machine learning models directly on the smartphone's neural processing unit (NPU) rather than sending requests to cloud servers. Google's Gemini Nano, accessed via the AI Edge SDK, enables this for Android devices (currently Pixel 9 and expanding to other devices).
On-device processing solves three problems: latency (no network round trip), cost (no per-inference cloud charges), and privacy (sensitive data never leaves the device). Apps can function offline, process health or financial data privately, and respond instantly to user actions.
A2UI (Agent-to-User Interface) is Google's open standard for enabling AI agents to generate user interfaces. Instead of outputting text or attempting to generate code, AI agents send structured JSON payloads describing component trees. The client application interprets these payloads and renders native UI elements.
The protocol enforces a strict separation of concerns: the AI agent determines what to show based on user intent; the client application determines how it's rendered. Flutter's GenUI SDK provides the concrete implementation, making it straightforward to add GenUI capabilities to Flutter apps.
Generative UI is an architecture where AI generates user interface components dynamically rather than displaying pre-built static screens. The AI sends a declarative payload describing what to show (a carousel of restaurant cards, a booking form, a comparison table). The app renders these using native widgets from a pre-approved component registry.
GenUI eliminates the "chat disappointment" where users tire of reading long text responses. It also provides security: since the AI sends data, not code, prompt injection attacks cannot generate malicious interfaces. The app retains control over what can be rendered.
AI-native development means AI shapes the entire user experience, not just a chat interface bolted onto an existing app. The AI determines what UI components to display based on user intent. Instead of typing messages back and forth, users interact with forms, cards, sliders, and controls that appear dynamically.
This approach uses technologies like Google's A2UI protocol with Flutter. When someone asks to book a flight, the app generates a booking form with native date pickers and seat selectors. The AI decides the structure. Flutter renders it instantly. User frustration with "walls of text" disappears.
The best apps come from close partnership. You'll work with us as an extension of your team: your vision drives every decision while our mobile app development experience guides you around common pitfalls.
70% of app projects fail due to misaligned expectations and market misunderstanding. The App Gameplan catches these issues before you've committed significant budget.
Start with a 30-minute call. No pressure, no sales pitch. Just an honest conversation about your project.
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Laying the Foundation for Success
It's your concept, your dream. You'll share your vision, target audience, and business objectives. We'll listen, research, and recommend until we've transformed your initial idea into a clearly defined mobile app concept.
You'll get competitive analysis that identifies opportunities and potential challenges. We'll outline key features and create a detailed project roadmap together.
Thorough planning and research are crucial for mitigating risks, ensuring a smooth development process, and maximising your app's chances of success.
Creating an Engaging and Intuitive Experience
Good design drives engagement and retention. You'll work with our in-house designers to map the user journey, ensuring intuitive navigation throughout. We design wireframes and mockups so you can visualise the product before any code is written. Once we've agreed on core functionality, you'll test high-fidelity interactive prototypes on a real device with real users.
You'll validate ideas before committing to development. Interactive prototypes catch usability issues early, when they're cheap to fix.
Building Future-Proof Code You Can Scale
Your design becomes a working app. We use Flutter with industry best practices to build scalable, maintainable code that grows with your business. Easy updates, straightforward feature additions. Every app undergoes rigorous automated and manual testing across multiple devices and platforms before you see it.
Your app won't become technical debt. Our architecture and documentation standards make it a valuable business asset that's cost-effective to maintain and enhance.
Ensuring Long-Term Success Through Partnership
You'll get guidance through App Store submission, ensuring your app meets all requirements and regulations. We work with you on App Store optimisation to increase visibility and drive downloads. After launch, we proactively monitor performance, address issues quickly, and collaborate on updates and enhancements.
Your app's success doesn't end at launch. Ongoing support maximises reach, generates revenue, and builds long-term success.
Your app, your way. Here's how we make it happen.
Our process begins with a comprehensive project plan and a transparent, fixed cost agreement. This ensures you know exactly what you're getting and how much it will cost, eliminating any unwelcome financial surprises. Regular progress calls with live demos give you a front-row seat to your app's development, keeping you informed and involved at every stage.
We're not just here for the build, we're here for the long haul. From navigating the App Store maze to providing ongoing technical support, we're with you all the way. Our expertise doesn't end at launch; we offer cost-effective maintenance plans and helpful guidance to ensure your app continues to thrive and evolve with your business. Your success is our success, and you can count on us every step of the way.
We believe the best apps are born from real user experiences. That's why user testing is at the core of everything we do. We involve real people from your target audience throughout the development process to ensure your app is intuitive, engaging, and truly meets their needs. Their honest feedback helps us to refine and enhance your app, resulting in a product that's not only user-friendly but loved by your users.
You know your business inside and out and we know how to make successful tech businesses. With years of hands-on CTO and app development experience, we're experts at understanding your needs and crafting innovative solutions that fit your budget and exceed expectations. Our collaborative process and hands-on prototyping ensure your final product isn't just an app – it's the realisation of your vision.
Our founder has been making mobile apps since 2003, before they were even called apps! Founded in 2017, we've got quite a few projects under our belt and a wealth of experience to call upon. Our core development team have been with us since the start, and one of the reasons we're considered the most experienced Flutter app development company in the UK.
We believe in the power of face-to-face collaboration. That's why we encourage you to visit us at our Manchester offices whenever you like. We're a friendly bunch, and we thrive on the energy and clarity that comes from an in-person chat. Building strong relationships is key to our collaborative approach, and we want you to feel comfortable dropping by for a brainstorming session, or just for a brew if you fancy.
