Supermemory
by supermemoryai
Lightning-Fast Memory Layer for AI Applications
Build AI apps with persistent, scalable memory using Cloudflare's edge infrastructure and modern TypeScript tooling.
- 15,063+ GitHub stars
- Built with TypeScript
- Edge-deployed memory engine with global low-latency access via Cloudflare Workers
- MIT License license
About This Project
Supermemory provides a production-ready memory infrastructure designed specifically for AI applications that need to retain context across sessions. Built on Cloudflare's global edge network, it delivers sub-100ms query times while handling massive scale through distributed KV storage and Postgres integration.
The project combines Remix for the frontend, Drizzle ORM for type-safe database operations, and Cloudflare Workers for serverless compute to create a complete memory solution. Developers can store, retrieve, and search through conversation history, user preferences, and contextual data without managing complex infrastructure.
What sets this apart is its edge-first architecture that eliminates traditional database latency bottlenecks. The memory engine automatically indexes and organizes data for fast retrieval, making it ideal for chatbots, AI assistants, and any application where context persistence directly impacts user experience.
With full TypeScript support and modern tooling like Vite and TailwindCSS, the codebase is developer-friendly and ready for customization. The combination of serverless deployment and pay-per-use pricing makes it cost-effective for projects of any size.
Key Features
- Edge-deployed memory engine with global low-latency access via Cloudflare Workers
- Hybrid storage combining Cloudflare KV for speed and Postgres for complex queries
- Type-safe database operations through Drizzle ORM with full TypeScript support
- Production-ready web interface built with Remix, Vite, and TailwindCSS
- Serverless architecture enabling automatic scaling without infrastructure management
How You Can Use It
Building conversational AI chatbots that remember user context across multiple sessions
Creating personalized AI assistants that learn from user interactions and preferences
Developing customer support systems with persistent conversation history and knowledge bases
Implementing AI-powered applications that require fast access to historical user data and context
Who Is This For?
Full-stack developers and AI engineers building conversational applications, chatbots, or intelligent systems requiring persistent memory and context management