Memvid

Hey Product Hunt family 👋 We’re excited to introduce Memvid V2, a new approach to AI memory designed to eliminate the complexity of traditional RAG pipelines and vector databases. Memvid gives AI agents long-term, persistent memory in a single portable file, with sub-5ms retrieval, zero infrastructure, and full offline support. If your agent can read a file or call a function, it can now remember across sessions, without managing databases, indexes, or fragile retrieval stacks. Memvid stores memory as self-contained “Smart Frames” that combine content, embeddings, timestamps, and relationships. This allows hybrid semantic, keyword, and temporal search in one unified system. The result is faster retrieval, lower costs, and significantly higher accuracy compared to conventional RAG setups, while remaining fully model-agnostic across GPT, Claude, Gemini, Llama, and modern agent frameworks. Alongside V2, we’re also releasing several open-source tools built on top of Memvid to help developers capture architectural decisions, build AI apps quickly, persist coding context, and rewind code history, all with the same portable memory foundation. We built Memvid because AI memory has been unnecessarily complex for too long. This launch is about simplifying that layer entirely. We’d love your feedback, questions, and ideas. Go to Memvid.com