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 ajoute une mémoire et un contexte persistants aux agents IA via API, plugins et applications.
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.
Supermemory indexes text, conversations, and files, then builds a semantic understanding graph on top of entities such as users, documents, projects, and organizations.
It combines memory, retrieval, and user profiles in a single queryable graph so agents can fetch relevant context when needed.
The retrieval layer supports hybrid search, reranking, and structured context, with sub-300ms latency called out on the site.
The product includes connectors for sources such as Slack, Notion, Drive, Gmail, GitHub, and S3, and keeps them in sync automatically.
Supermemory exposes a filesystem-style workflow where files can be indexed automatically and tools like ls, cat, and grep map to semantic context.
The platform can analyze memory in place to cluster, summarize, and explain user signals without exporting the dataset.
Build assistants that retain user preferences, prior facts, and conversation history across sessions so replies stay consistent over time.
Keep internal knowledge bases current by syncing documents and sources, then retrieving fresh context instead of relying on stale snapshots.
Connect tools such as Drive, Gmail, GitHub, or Slack and use them as part of an agent’s working memory without manual imports.
Use the filesystem-style workflow to let agents browse and reason over indexed files with familiar commands like ls, cat, and grep.
Run on-prem, in your cloud, or in an air-gapped environment when memory infrastructure needs to stay inside a defined security boundary.
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.
The docs describe Supermemory as handling text, conversations, files such as PDFs, images, and docs, and even videos through its extraction pipeline.
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.
The site says Supermemory can be used through its API, developer plugins, and a personal app, with SDKs for major languages and model harnesses.
The documentation and pricing pages indicate self-hosting is available on paid plans, with enterprise options for dedicated or air-gapped deployments.
Les données de trafic sont fournies à titre indicatif uniquement.
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