Supermemory — Universal Memory API for AI apps
Add long‑term memory to your LLM apps. Fast Memory API + Router. Store, recall, personalize in milliseconds.
What it is
Supermemory is a universal memory API designed for AI application developers and enterprises. It provides a long-term memory layer that enables AI agents and applications to remember user-specific context, preferences, and historical interactions across sessions. The service is built to be interoperable between different AI models and data modalities.
Main Features
Core Performance
- Sub-300 millisecond recall latency for memory retrieval
- Up to 10x faster recall time compared to alternatives like Zep
- Up to 25x faster performance than Mem0
- 70% lower infrastructure costs compared to enterprise-grade alternatives
Memory Management
- Graph-based indexing and enrichment linking related memories
- Memory evolution with updates, extensions, and expiration
- Automatic data cleaning and chunking for long-form text
- Support for structured and unstructured data
Data & Integration
- Multimodal data support including files, documents, chats, emails, and PDFs
- Connectors for Google Drive, Notion, OneDrive, and other platforms
- SDKs for OpenAI, Anthropic, AI SDK, Cloudflare, and other popular frameworks
Enterprise Capabilities
- SOC 2 compliance with data encryption in transit and at rest
- Flexible deployment options: cloud, on-premises, or hybrid
- Fine-grained access controls and admin dashboard for monitoring
- Redundant storage and enterprise-grade scalability
How it works
Integration Process
Developers integrate Supermemory into their AI applications using provided SDKs or API endpoints. The setup process is designed to take minutes, with connectors available for popular development frameworks and cloud platforms.
Data Processing Pipeline
Raw data from various sources (files, chats, documents) is ingested, automatically cleaned, and chunked. The system then applies advanced embeddings for semantic understanding and enriches memories using graph-based technology to link related information across applications and contexts.
Memory Recall & Evolution
Memories are indexed into both vector stores and graph databases for precision retrieval. The system provides semantic and keyword search capabilities with sub-300ms recall times. Memories continuously evolve through updates, extensions, and automatic expiration to maintain relevance.
Key Points
- The platform is designed to mimic human brain functionality with features like forgetfulness and contextual understanding
- Customers report significant improvements in search performance (3x), recall accuracy (60%), and task completion speed
- The service enables personalized AI experiences by maintaining persistent user context across interactions
- Recent $3M funding round indicates strong investor confidence and company growth trajectory
Additional Details
Pricing Tiers
- Free: $0/month with 1M tokens processed, 10K search queries, and email support
- Pro: $19/month with 3M tokens processed, 100K search queries, priority support, and advanced analytics
- Scale: $399/month with 80M tokens processed, 20M search queries, dedicated support, custom integration, and Slack support channel
Availability
- API access for developers and enterprises through console.supermemory.ai
- Separate Supermemory App for individual users at app.supermemory.ai
- Comprehensive documentation available at supermemory.ai/docs
Technical Requirements
- Supports TypeScript, Python, and cURL for integration
- Works with various AI models and frameworks
- Requires API integration through provided SDKs or direct API calls
