supermemory™

Supermemory offers a universal memory API for AI applications, enabling personalized large language models, unlimited context management, and simplified information retrieval.

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About supermemory™

Supermemory is a versatile memory API designed for the AI era, allowing developers to integrate automatic long-term context into applications. It eliminates the need to build retrieval systems from scratch by providing an API that supports unlimited context for large language models. Built for enterprise use, it ensures high performance at any scale, seamless team collaboration, and data ownership with flexible deployment options including cloud, on-premises, or on-device. Compatible with any LLM provider, Supermemory maintains sub-400ms latency while delivering exceptional accuracy and recall.

How to Use

Integrate Supermemory's API or SDKs into your applications to enhance functionality. To add memories, send a POST request to https://api.supermemory.ai/v3/memories with your data (text, URL, PDF). Search memories by making a GET request with your query. Connect external tools like OneDrive via dedicated endpoints. For OpenAI integration, update your API base URL to connect through Supermemory for unified long-term context. SDKs for Python and JavaScript simplify implementation, with commands like 'pip install supermemory' and 'npm install supermemory'.

Features

Universal memory API tailored for AI applications

Seamless integration with tools like Notion, Google Drive, and CRMs

Supports unlimited context for large language models

Compatible with AI SDKs, Langchain, and other frameworks

Language-agnostic SDKs for Python and JavaScript

Achieves sub-400ms latency at enterprise scale

Model-agnostic API compatible with any LLM provider

Delivers high-precision retrieval performance

Secure, flexible deployment options including cloud, on-premises, and on-device

Handles billions of data points with low-latency access

Use Cases

Implementing long-term conversation context in AI chatbots

Building scalable memory infrastructure without starting from scratch

Personalizing LLMs for individual users

Creating writing assistants with persistent memory

Indexing large volumes of documents, videos, or product data

Powering co-intelligent platforms for enterprise clients

Integrating with existing data sources like Notion and Google Drive

Enabling search across extensive vendor databases in Medtech

Best For

Medtech vendorsDevelopersOpen source projectsAI platform buildersEnterprise organizations

Pros

Quick deployment with SDKs for Python and JavaScript, enabling setup within days.

Provides superior precision and recall compared to competitors.

Ensures enterprise-grade scalability and low latency for billions of data points.

Full control over data with secure, flexible deployment options.

Enables personalized LLMs for improved user experiences.

Supports automatic long-term context across conversations.

Vendor-neutral APIs facilitate easy switching between LLM providers.

Addresses common challenges like slow vector searches and format issues.

Reduces development time by eliminating the need to build retrieval systems.

Integrates effortlessly with existing tools and data sources.

Offers unlimited context for richer AI interactions.

Delivers fast, scalable retrieval with optimized RAG techniques.

Frequently Asked Questions

Find answers to common questions about supermemory™

What exactly is Supermemory?

Supermemory is a universal memory API that helps developers personalize LLMs and manage long-term context without building retrieval systems from scratch.

How does Supermemory manage context for AI models?

It provides an unlimited context API, enabling automatic long-term conversation memory and easy integration with LLMs by updating the API base URL.

What types of data can Supermemory handle?

Supermemory indexes various formats, including documents, videos, structured data, PDFs, Word files, images, and audio/video, supporting diverse data sources.

Is Supermemory suitable for large-scale applications?

Yes, it is designed for enterprise use, capable of handling billions of data points with low-latency retrieval to ensure performance at scale.

Can Supermemory be deployed on-premises?

Absolutely. It offers flexible deployment options, including cloud, on-premises, and on-device setups for maximum data control.

Does Supermemory work with any large language model?

Yes, its model-agnostic APIs allow compatibility with any LLM provider, avoiding vendor lock-in.

How fast is Supermemory in real-world scenarios?

Supermemory achieves sub-400ms latency at scale, ensuring quick responses for demanding AI applications.

What integrations are available with Supermemory?

It seamlessly connects with tools like Notion, Google Drive, and CRMs, and supports SDKs for Python and JavaScript for easy development.