Your Go-To Blog on React Native, AI & Multimedia

At Software Mansion, we’ve created various AI tools like React Native ExecuTorch, which allows you to run AI models declaratively on-device. We’ve also built React Native RAG, which offers native support for Retrieval-Augmented Generation, and Private Mind, a private assistant app that showcases the possibilities of the libraries mentioned above.

In the previous part of our series, we’ve added web search and intelligent shutdown to our chatbot to explore tools and structured output.

In the previous parts of our series, we’ve explored the key concepts behind building AI agents with LangChain and LangGraph, and we’ve constructed a fully-functional AI chatbot along the way. Today, we’re diving into a case study from the development of our very own marketing agent.

As mentioned in my Demuxed 2025 recap blogpost, I had the pleasure of delivering a lightning talk about a side project I’ve been working on: automatic knowledge extraction from the H.264 specification. Today, I would like to delve deeper into this topic, sharing more details than I could during the brief three-minute talk.

In the previous part of our series, where we’re building an AI-powered note-taking app, we implemented a local RAG (Retrieval-Augmented Generation) assistant that lets you chat with your notes privately and offline.

Welcome to our series where we’re building an AI note-taking app in React Native, making it fully private & local. In the previous parts, we focused on giving the app a deep understanding of your notes — combining text and images through local multimodal embeddings.

In the previous part of this series, we added semantic text search to our React Native note-taking app, letting users find notes by meaning, not just keywords.