Do you build computer vision and voice AI features?

Yes. Vision covers document OCR, object detection, barcode and label scanning, and camera copilots using on-device or cloud vision APIs. Voice includes speech-to-text, text-to-speech, and voice agents with wake-word optional. We design permission flows and fallback when camera or mic access is denied.

How long does AI mobile app development take?

MVP AI features (chat plus one capability) often ship in 8 to 12 weeks: discovery and architecture in weeks 1-2, UX and API design in weeks 3-4, build and model tuning in weeks 5-8, QA and store prep in weeks 9-12. Full greenfield AI apps with vision, RAG, and on-device ML may run 14 to 20 weeks.

Cloud LLM vs on-device ML: which should we choose?

Cloud LLMs excel at reasoning, long context, and rapid model upgrades but add latency and per-token cost. On-device ML excels at privacy, offline use, and predictable latency with no API bill. Hybrid routing sends sensitive or repetitive tasks on-device and complex queries to cloud. We recommend based on your SLA, budget, and compliance needs.

Native Swift/Kotlin vs React Native for AI apps?

Native delivers best Core ML and low-level camera or audio access. React Native and Flutter work well when AI is mostly API-driven chat with standard plugins. We match stack to your team and feature mix: heavy on-device ML often favors native; chat-first MVPs often ship faster on cross-platform.

How do you control AI API costs in production?

We implement token budgets per user, caching for repeated queries, smaller models for draft responses, streaming to improve perceived speed without extra calls, and dashboards on cost per session. Prompt compression and RAG chunk limits reduce input tokens. Growth plans include monthly cost reviews.

What happens after our AI mobile app launches?

You receive 30 days of post-launch support, model version migration notes, and monitoring setup. Optional retainers cover prompt tuning, new model upgrades, embedding refreshes for RAG, and App Store compliance updates. We cross-link web AI services when you need automation beyond the app.

AI Mobile App Development ★ 4.9 · 47 reviews

AI Mobile App Development.
GPT & On-Device ML Built In.

GPT-4o chat, Core ML inference, computer vision, and voice agents. built into native iOS and Android apps.

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32+ AI apps shipped

1.4s avg. response time

3x avg. engagement lift

Vision Active RAG Active

Summarize this invoice for my expense report.

GPT-4o Claude On-Device

Models

Tokens/s

Route

Cloud

32+

AI Apps Shipped

1.4s

Avg AI Latency

Engagement Lift

Models Integrated

AI Mobile Signals

Four Signals That Make AI Mobile Apps Feel Native and Fast.

Model Routing

GPT-4o, Claude, Gemini, or on-device Core ML chosen per task for cost, speed, and privacy.

Streaming Latency UX

Token-by-token UI, skeleton states, and 1.4s target perceived response on mobile networks.

Privacy Boundaries

On-device inference for PII, regional endpoints, and App Store nutrition label documentation.

RAG Context

Vector retrieval from your docs and catalog so answers cite real sources, not hallucinations.

Build Process

From AI Discovery to App Store Launch in 8 to 12 Weeks.

Week 2

Week 6

W10

Week 10

Ongoing

Discovery & Routing

Use cases, model map (GPT, Claude, Core ML, TFLite), privacy review, and latency targets before UI design.

AI UX & Prompts

Streaming chat flows, vision capture screens, voice states, and prompt templates approved on device mockups.

Build & Integrate

Native or cross-platform app with API proxy, RAG pipeline, on-device models, and analytics on token usage.

Launch & Tune

Store submission, cost dashboards, prompt tuning, and embedding refresh for RAG knowledge apps.

AI Mobile App Plans

Choose Your AI Mobile App Development Level.

Quote-based plans. No long-term contracts. Scoped by model integrations, on-device ML, RAG scope, and design complexity.

STARTER

Starter

MVP chat ï¿½ One AI capability

?AI use-case & model audit
?1 AI feature MVP (chat or vision)
?GPT / Claude integration
?RAG or on-device ML scope
?Streaming chat UX
?30-day reporting

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What Professional AI Mobile App Development Delivers.

AI Apps Shipped

Avg AI Latency

Engagement Lift

Models Integrated

GPT, Claude, Gemini, on-device

Our field app had no AI. Groke added on-device OCR with Core ML and a GPT-4o copilot for summaries.

Product Lead, Field Service App (Canada)

FAQ

Common questions.

Which GPT or Claude models do you integrate in mobile apps?

We integrate OpenAI GPT-4o and GPT-4o mini, Anthropic Claude 3.5 Sonnet and Haiku, Google Gemini, and open-source models via API or self-hosted endpoints. Model choice depends on latency budget, cost per token, and whether responses need vision or tool use.

Do you build on-device ML with Core ML or TensorFlow Lite?

Yes. For iOS we ship Core ML and Create ML pipelines for classification, segmentation, and on-device embeddings.

How do you handle AI privacy and data on mobile?

We map data flows before build: what leaves the device, what is encrypted in transit, and what is stored. On-device inference keeps PII local.

How much does AI mobile app development cost?

AI mobile app development is quote-based across Starter, Growth, and Scale plans depending on model integrations, on-device ML scope, RAG infrastructure, and design complexity. No fixed public pricing. Written quote within 48 hours of your discovery call. Month-to-month available.

What is RAG in a mobile app context?

Retrieval-Augmented Generation (RAG) lets your app answer from your documents, product catalog, or support knowledge base instead of model training alone. We embed content, retrieve relevant chunks at query time, and stream grounded answers in the chat UI.

Can you add an AI chatbot to an existing mobile app?

Yes. We integrate chat SDKs, streaming UI, auth, rate limits, and admin dashboards into existing native or cross-platform apps.

Ready to Convert More Visitors?

Get a Free AI Mobile App Scope Call - Map Models, Privacy, and Timeline.

Free 30-min AI mobile scope call. We review your use cases, model options (GPT, Claude, Core ML, TensorFlow Lite), RAG needs, privacy constraints, and timeline - and show you what a production AI app architecture looks like before any commitment.

Free AI scope call - 30 minutes, no obligation

Full scope and pricing delivered within 48 hours

Month-to-month - no long-term contracts required

Development starts within 5 business days of sign-off

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Average response: under 4 hours ï¿½ Serving US, UK, CA, AU

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Further reading: Apple HIG Â· Material Design 3

AI Mobile App Development.GPT & On-Device ML Built In.