I will develop cross platform flutter ai app with custom rag and ai agents


About this gig
Most Flutter AI apps fail because developers treat AI as a basic API integration. They plug in an API key, ignore vector retrieval, and deliver a laggy chat interface that hallucinates, leaks context, and burns through your token budget.
I engineer production grade, cross platform Flutter AI applications built on robust backend architectures.
Whether you need a custom document-based RAG system (PDF, web data, SQL), a streaming AI assistant, or complex multi-agent workflows, I deliver scalable, secure apps for iOS, Android, and Web.
WHAT I BUILD:
- Flutter Cross-Platform UI (Clean Riverpod/Bloc Architecture)
- Custom RAG Systems (LangChain, LangGraph, LlamaIndex)
- Vector Database Pipelines (Pinecone, Supabase pgvector, Qdrant)
- Real-time Streaming UI (Sub-second response token rendering)
- Multi-modal Capabilities (Vision, Audio Transcriptions, TTS)
- Cost-Optimized Token & Context Window Management
HOW IT WORKS:
- Architecture Alignment & Data Scoping
- Vector Pipeline & Backend API Engineering
- Responsive Flutter UI & State Integration
- Rigorous Testing & App Build Delivery
Let's build an intelligent, production-ready mobile application that scales. Message me to review your project scope
Get to know JERE J
Expert AI Mobile App Developer, Flutter, React Native And OpenAI
- FromUnited Kingdom
- Member sinceSep 2026
Languages
English
FAQ
What do I need to provide before we start?
You will need a clear description of your app concept, your desired user flow, and access to your OpenAI or relevant AI/vector database API keys (or we can set them up together).
Will the app run smoothly on both iOS and Android?
Yes. I build using native Flutter state management practices (Riverpod/Bloc) to ensure responsive UI rendering and sub-second streaming response times on both platforms.
Can the app answer questions based on my private company documents?
Yes. I implement a Retrieval-Augmented Generation (RAG) architecture using vector databases like Pinecone or Supabase. This grounds your AI in your specific PDFs, documents, or database tables with high accuracy.
