Ingestion and semantic indexing
Supermemory indexes text, conversations, and files, then builds a semantic understanding graph on top of entities such as users, documents, projects, and organizations.
Supermemory
Freemium
Supermemory adds persistent memory and context to AI agents via API, plugins, and apps.
What is Supermemory?
Supermemory is a memory and context infrastructure product for AI agents. The site describes it as a long-term and short-term memory layer that helps developers give agents persistent recall about users, documents, projects, and organizational context.
It combines memory, retrieval, content extraction, connectors, and user profiles into one platform. The product is offered through a developer API, plugins, a personal app, and enterprise deployment options, with a pricing model based on usage rather than fixed seat licensing.
What can Supermemory do?
Unified memory graph
It combines memory, retrieval, and user profiles in a single queryable graph so agents can fetch relevant context when needed.
Low-latency SuperRAG
The retrieval layer supports hybrid search, reranking, and structured context, with sub-300ms latency called out on the site.
Connectors and syncing
The product includes connectors for sources such as Slack, Notion, Drive, Gmail, GitHub, and S3, and keeps them in sync automatically.
Filesystem mode for agents
Supermemory exposes a filesystem-style workflow where files can be indexed automatically and tools like ls, cat, and grep map to semantic context.
Qualitative analysis
The platform can analyze memory in place to cluster, summarize, and explain user signals without exporting the dataset.
Use Cases
“Persistent AI assistants”
Build assistants that retain user preferences, prior facts, and conversation history across sessions so replies stay consistent over time.
“Live knowledge retrieval”
Keep internal knowledge bases current by syncing documents and sources, then retrieving fresh context instead of relying on stale snapshots.
“Connected workspace context”
Connect tools such as Drive, Gmail, GitHub, or Slack and use them as part of an agent’s working memory without manual imports.
“Agent filesystem workflows”
Use the filesystem-style workflow to let agents browse and reason over indexed files with familiar commands like ls, cat, and grep.
“Controlled enterprise deployment”
Run on-prem, in your cloud, or in an air-gapped environment when memory infrastructure needs to stay inside a defined security boundary.
Frequently Asked Questions
What does Supermemory do?
Supermemory provides a memory and context layer for AI agents. It ingests text, chats, files, and other content, then indexes and retrieves relevant context at query time.
What kinds of content can it ingest?
The docs describe Supermemory as handling text, conversations, files such as PDFs, images, and docs, and even videos through its extraction pipeline.
How does pricing work?
The pricing page says plans start free with monthly usage included, and paid plans use monthly balances, usage-based billing, and optional auto top-up.
Who is it built for?
The site says Supermemory can be used through its API, developer plugins, and a personal app, with SDKs for major languages and model harnesses.
Can Supermemory be self-hosted?
The documentation and pricing pages indicate self-hosting is available on paid plans, with enterprise options for dedicated or air-gapped deployments.
Quick Facts
- Category
- AI agent memory / developer tool
- Primary users
- Developers, teams, and agent builders
- Deployment
- Cloud, self-hosted, and enterprise air-gapped options
- Pricing model
- Usage-based plans with a free starting tier
- Source domain
- supermemory.ai
- Notable workflow
- Ingest, understand, retrieve, and traverse context in a single graph
Supermemory Traffic Analysis
Traffic data is for reference only.
- Domain Rating
- 67
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