Give AI agents state-of-the-art, dynamic memory and context
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Tracked since2026
0 reviews trackedThe Bottom Line
Entry price
Free plan available, paid tiers above
Biggest pro
Enables agents to have state-of-the-art, evolving memory beyond simple vector storage.
Biggest con
Requires technical expertise for integration and development of AI agents.
TL;DR - Supermemory
- Provides state-of-the-art memory and context infrastructure for AI agents.
- Offers dynamic, persistent, and structured knowledge graphs for continual learning and user understanding.
- Integrates RAG, user profiles, and data connectors with low-latency retrieval across various data sources.
Pricing: Free plan available
Best for: Growing teams
What is Supermemory?
Supermemory provides a comprehensive context cloud for AI agents, offering advanced memory, Retrieval Augmented Generation (RAG), user profiles, and data connectors. It is designed to give agents state-of-the-art memory capabilities, allowing them to continually learn, understand, and retrieve information with extremely low latency. The platform integrates various primitives for ingesting, understanding, routing, and retrieving context, all built around a custom knowledge graph engine.
This platform is ideal for developers and teams building sophisticated AI agents that require persistent, structured, and evolving knowledge. It supports a wide range of data sources through connectors and extractors, automatically keeping agent memory in sync with external tools. Supermemory differentiates itself from traditional vector databases by offering dynamic knowledge that can merge, contradict, and evolve across sessions, ensuring agents remember users and contexts coherently over time. It offers a single API for all capabilities, including ingestion, retrieval, and memory management, and is designed for high performance with sub-300ms recall latency.
Pros & Cons
Pros
- Enables agents to have state-of-the-art, evolving memory beyond simple vector storage.
- Offers extremely low latency for context retrieval, crucial for real-time agent interactions.
- Simplifies context management with a single API for ingestion, retrieval, and memory.
- Provides robust data ingestion and extraction capabilities for various formats and sources.
Cons
- Requires technical expertise for integration and development of AI agents.
- Pricing is usage-based, which can be unpredictable for very high-volume applications without careful monitoring.
Preview
Key Features
Persistent and structured knowledge graph memoryHybrid search and reranking for Retrieval Augmented Generation (SuperRAG)Real filesystem mount for semantic search and live profile synthesisCoherent user profiles for consistent agent understanding across sessionsReal-time data synchronization with connectors (Slack, Notion, Drive, Gmail, GitHub, S3)Multimodal extractors for PDFs, web pages, images, audio, and raw filesQualitative analysis for clustering, summarizing, and explaining user signalsSub-300ms graph traversal for real-time context retrieval
Pricing Plans
Pricing checked Jun 6, 2026
Personal Supermemory Free
$0 / mo
- $5/mo of usage built in
- Hermes Plugin Supermemory MCP
- Community support
Pro
$19 / mo
- ~$20/mo of usage built in
- Unlimited storage
- Unlimited users
- Auto top-up available
- Buy additional usage
- Google Drive, Notion & OneDrive connectors
- 2 teammates included
- OpenClaw, Claude Code and other plugins
Max
$100 / mo
- ~$130/mo of usage built in (6× Pro)
- Unlimited storage
- Unlimited users
- Gmail connector
- Granola connector
- Auto top-up available
- OpenClaw, Claude Code and other plugins
- Priority support
Scale
$399 / mo
- ~$600/mo of usage built in
- Unlimited storage
- Unlimited users
- Up to 10 teammates
- All connectors (Gmail, GitHub, S3, Web Crawler + Pro)
- Auto top-up + spend caps
- Priority support
- SOC 2 · HIPAA BAA
Enterprise
Custom
- Security & compliance
- Air-gapped self-hosting - you own the data.
- Dedicated managed instance
- SOC 2 · HIPAA · GDPR
- Custom contracts & DPA
- Enterprise MCP
- Scale & performance
- ~Unlimited usage
How Supermemory's pricing compares
At $19/mo, Supermemory is the most affordable of its 3 direct competitors.
Entry paid plan, monthly. Pricing checked Jun 6, 2026.
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Supermemory FAQ
How does Supermemory's memory system differ from a traditional vector database?
Supermemory's memory system goes beyond storing chunks by providing facts that evolve, knowledge that merges, contradicts, and can be forgotten across sessions. It uses user profiles and an ontology-aware graph to enable updates, merges, contradictions, and inferences, offering a more dynamic and coherent understanding compared to the static nature of vector databases.
What is 'Dynamic Dreaming' and how does it contribute to agent memory?
Dynamic Dreaming is a core component of Supermemory's custom user understanding model. It powers the knowledge graph, allowing for continual learning and the dynamic evolution of persistent, structured memory, enabling agents to synthesize context on the fly and maintain a live profile.
Can Supermemory integrate with existing data sources and keep them updated automatically?
Yes, Supermemory offers Connectors for popular platforms like Slack, Notion, Google Drive, Gmail, GitHub, and S3, as well as custom sources. These connectors automatically keep data in sync, reflecting changes in external tools in real-time within the agent's memory without manual imports or ETL processes.
How does Supermemory handle different file formats for agent-ready memory objects?
Supermemory's Extractors can turn various file formats, including PDFs, web pages, images, audio, and raw files, into agent-ready memory objects. It employs smart chunking that preserves meaning across document boundaries, eliminating the need for multiple third-party providers for extraction.
What is an 'SM token' and how does it relate to billing?
An SM token represents unique content that Supermemory ingests and embeds. Billing is based on these unique SM tokens, with a 100% discount for repeated or unchanged content. This means re-uploading the same document or syncing unchanged data does not incur additional costs, making it cost-effective for agents that loop over the same context.
Is it possible to self-host Supermemory for specific deployment needs?
Yes, self-hosted deployments are available for larger plans. This option also supports fully air-gapped deployments, with leading AI model inference potentially being the only outbound dependency, unless local GPU resources are available.
How does Supermemory ensure low latency for retrieval and graph traversal?
Supermemory is engineered for high performance, achieving sub-300ms recall latency for its SuperRAG system and sub-300ms graph traversal for every request. This is achieved through its custom graph engine and optimized architecture, allowing agents to access the knowledge graph in real-time during requests.
What kind of qualitative analysis capabilities does Supermemory offer for user signals?
Supermemory provides qualitative analysis features that allow users to cluster, summarize, and explain user signals directly against their memory. This understanding layer runs in-place, ensuring data privacy as the data never leaves the user-defined boundary.
Source: supermemory.ai