AI-Powered Mobile App Developer Denver — OpenAI, Claude & On-Device ML
LLM API integration (OpenAI, Claude/Anthropic, Google Gemini), on-device inference (Core ML, MediaPipe, llama.cpp), prompt engineering, cost controls, and privacy guardrails — all shipped in production mobile apps. Current product: AIBuddy (iOS/macOS/Windows AI assistant with local LLM support).
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AI-Powered Mobile Apps — Frequently Asked Questions
How do I add ChatGPT or Claude to my mobile app?
LLM API integration involves a backend proxy (so your API keys never ship in the app binary), a streaming response handler, a token cost ledger, and rate-limiting guardrails. The mobile app sends a request, the proxy calls the LLM API, and the response streams back to the UI. The AIBuddy product uses this pattern across iOS, macOS, and Windows with sub-$0.01 per-query economics.
Can AI features run on the device without an internet connection?
Yes, for certain tasks. Apple Core ML and Google MediaPipe run fully on-device — classification, object detection, and speech recognition work offline. For conversational AI, on-device is possible with smaller models (Llama 3 8B, Phi-3) using llama.cpp, but response quality is lower than cloud APIs and first-run model download is large (4-8 GB).
How much does it cost to add AI features to a mobile app?
AI integration typically adds $15,000-$40,000 to a mobile project depending on feature depth. A single LLM-powered feature (in-app chat, content summarization, recommendation) is on the low end. A full AI assistant with streaming, history, tool use, and on-device fallback is on the high end.
How do you prevent AI features from leaking user data?
Privacy guardrails include: never sending PII in prompt context (strip or anonymize before the API call), backend proxy so API keys are server-side only, optional on-device model path for sensitive data, and prompt injection defense. HIPAA-adjacent projects receive a data-flow diagram before any AI work starts.
What AI APIs and models do you have production experience with?
Production experience: OpenAI (GPT-4o, GPT-4-turbo, o1, DALL-E, Whisper, gpt-image-1), Anthropic Claude (claude-3-5-sonnet, claude-opus-4), Google Gemini, AWS Bedrock, and local inference via llama.cpp / LM Studio. The AIBuddy product ships all of these through a unified provider abstraction.
