supermemory™

How does Supermemory handle context for LLMs? What kind of data can Supermemory handle? Is Supermemory scalable? Can Supermemory be deployed on-premise? Does Supermemory work with any LLM? How fast is Supermemory? What integrations does Supermemory support? supermemory™

## Key Features

- Universal memory API for the AI era - Unlimited context API for LLMs - Enterprise-Grade Performance at Any Scale (billions of data points, low-latency retrieval) - Seamless Integration Across Teams & Tools (Notion, Google Drive, CRMs) - Secure by Design, Fully Controllable deployment (cloud, on-prem, on-device) - Model-agnostic APIs (works with any LLM provider) - Sub-400ms latency at scale - Best in class performance (stronger precision and recall) - Works with AI SDK, Langchain, and more - Language Agnostic SDKs (Python, Javascript)

## Use Cases

- Personalizing LLMs for users. - Adding automatic long-term context across conversations for agentic apps. - Building memory infrastructure without starting from scratch. - Indexing documents, video, or structured product data at scale. - Connecting to existing data sources like Notion, Google Drive, and custom CRMs. - Flow uses Supermemory to build the cursor for writing. - Medtech Vendors use Supermemory to search through 500k vendors. - Mixus uses Supermemory to power co-intelligence Agentic platform.