diff --git a/apps/docs/docs.json b/apps/docs/docs.json index 47d44c75..90f4049b 100644 --- a/apps/docs/docs.json +++ b/apps/docs/docs.json @@ -72,17 +72,17 @@ "pages": ["intro", "quickstart", "vibe-coding"] }, { - "group": "Command Line (CLI)", - "icon": "square-terminal", - "pages": ["cli/overview", "cli/commands", "cli/local"] - }, - { - "group": "Self-Hosting", + "group": "Core Features", "pages": [ - "self-hosting/overview", - "self-hosting/quickstart", - "self-hosting/configuration", - "self-hosting/local-vs-enterprise" + "add-memories", + "search", + "user-profiles", + { + "group": "Manage Content", + "icon": "folder-cog", + "pages": ["document-operations", "memory-operations"] + }, + "overview/use-cases" ] }, { @@ -100,20 +100,6 @@ "authentication" ] }, - { - "group": "Using supermemory", - "pages": [ - "add-memories", - "search", - "user-profiles", - { - "group": "Manage Content", - "icon": "folder-cog", - "pages": ["document-operations", "memory-operations"] - }, - "overview/use-cases" - ] - }, { "group": "Connectors and sync", "pages": [ @@ -136,6 +122,30 @@ "memory-api/connectors/managing-resources" ] }, + { + "group": "Migration Guides", + "pages": [ + { + "group": "From another provider", + "icon": "truck", + "pages": ["migration/from-mem0", "migration/from-zep"] + } + ] + }, + { + "group": "Self-Hosting", + "pages": [ + "self-hosting/overview", + "self-hosting/quickstart", + "self-hosting/configuration", + "self-hosting/local-vs-enterprise" + ] + }, + { + "group": "Command Line (CLI)", + "icon": "square-terminal", + "pages": ["cli/overview", "cli/commands", "cli/local"] + }, { "group": "SMFS (Memory Filesystem)", "icon": "database", @@ -157,16 +167,6 @@ }, "smfs/examples" ] - }, - { - "group": "Migration Guides", - "pages": [ - { - "group": "From another provider", - "icon": "truck", - "pages": ["migration/from-mem0", "migration/from-zep"] - } - ] } ] }, diff --git a/apps/docs/intro.mdx b/apps/docs/intro.mdx index 319a55ea..c76b70ef 100644 --- a/apps/docs/intro.mdx +++ b/apps/docs/intro.mdx @@ -4,15 +4,34 @@ sidebarTitle: "Overview" icon: "book-open" --- -Supermemory is the long-term and short-term memory and context infrastructure for AI agents. It is the [state of the art](https://supermemory.ai/research) across multiple different benchmarks, like LongMemEval and LoCoMo. +Supermemory is the long-term and short-term memory and context infrastructure for AI agents. It is the [state of the art](https://supermemory.ai/research) across multiple benchmarks, including LongMemEval and LoCoMo. -With supermemory, developers can provide perfect recall about their users to build AI agents that are more intelligent, more personalized, and more consistent. Additionally, *supermemory* has all the pieces of the context stack built in: -- [Agent memory](/concepts/graph-memory) -- [Content extraction](/concepts/content-types) -- [Connectors and syncing](/connectors/overview) -- [Managed RAG platform](/concepts/super-rag) +With supermemory, you give your agents perfect recall about their users — so they're more intelligent, more personalized, and more consistent. Every piece of the context stack is built in, behind one API. -All this, coming together, makes supermemory the best abstraction to provide to agents. +## What you can build with it + + + + Extract and evolve facts about each user over time — knowledge updates, temporal changes, automatic forgetting. + + + A live blend of static and dynamic context your agent should always know, built automatically from memory. + + + Semantic search with metadata filtering, contextual chunking, and reranking — over memories and raw documents in one query. + + + Ingest text, conversations, PDFs, images, and even video — all turned into searchable, structured context. + + + Continuously pull from Google Drive, Notion, Gmail, OneDrive, and more, with no pipeline to maintain. + + + Production-grade retrieval as a service, tuned to work alongside the memory engine. + + + +All of it shares the **same context pool** for a given user (`containerTag`), so memory and search reinforce each other instead of living in separate silos. ## How does it work? (at a glance) @@ -22,68 +41,70 @@ All this, coming together, makes supermemory the best abstraction to provide to - Supermemory [intelligently indexes them](/concepts/how-it-works) and builds a semantic understanding graph on top of an entity (e.g., a user, a document, a project, an organization). - At query time, we fetch only the most relevant context and pass it to your models. -## Supermemory is context engineering. +## Supermemory is context engineering -#### Ingestion and Extraction +We offer three ways to add context to your LLMs — mix and match them as your use case needs. -Supermemory handles all the extraction, for [any data type that you have](/concepts/content-types). -- Text -- Conversations -- Files (PDF, Images, Docs) -- Even videos! - -... and then, - -We offer three ways to add context to your LLMs: - -#### Memory API — Learned user context +#### Memory API — learned user context ![memory graph](/images/memory-graph.png) -Supermemory learns and builds the memory for the user. These are extracted facts about the user, that: +Supermemory learns and builds memory for each user. These are extracted facts that: - [Evolve on top of existing context about the user](/concepts/graph-memory), **in real time** -- Handle **knowledge updates, temporal changes, forgetfulness** -- Creates a **user profile** as the default context provider for the LLM. +- Handle **knowledge updates, temporal changes, and forgetfulness** +- Power a **user profile** that acts as the default context provider for the LLM -_This can then be provided to the LLM, to give more contextual, personalized responses._ +_Provide this to your LLM for more contextual, personalized responses._ #### User profiles -Having the latest, evolving context about the user allows us to also create a [**User Profile**](/concepts/user-profiles). This is a combination of static and dynamic facts about the user, that the agent should **always know** -Developers can configure supermemory with what static and dynamic contents are, depending on their use case. +The latest, evolving context about a user also produces a [**User Profile**](/concepts/user-profiles) — static and dynamic facts the agent should **always** know: -- Static: Information that the agent should **always** know. -- Dynamic: **Episodic** information, about last few conversations etc. +- **Static:** information the agent should **always** know. +- **Dynamic:** **episodic** information about the last few conversations. -This leads to a much better retrieval system, and extremely personalized responses. +Configure what counts as static vs. dynamic for your use case for extremely personalized retrieval. -#### RAG - Advanced semantic search +#### RAG — advanced semantic search -Along with the user context, developers can also choose to do a search on the raw context. We provide full RAG-as-a-service, along with -- Full advanced metadata filtering +Alongside user context, run search over the raw content. Full RAG-as-a-service, with: +- Advanced metadata filtering - Contextual chunking -- Works well with the memory engine - - - See the full API Reference tab for detailed endpoint documentation. - - +- Tight integration with the memory engine -All three approaches share the **same context pool** when using the same user ID (`containerTag`). You can mix and match based on your needs. +All three approaches share the **same context pool** when using the same user ID (`containerTag`). Mix and match based on your needs. -## Next steps +## Start building - + - Make your first API call in minutes + Make your first API call in minutes. - - Understand the knowledge graph architecture + + Ingest text, files, and conversations into a container. - - Run Supermemory on your own machine — one binary, zero config, fully offline + + Retrieve the most relevant context with hybrid semantic search. +## Ways to use Supermemory + +The API is the core — but you don't have to talk to it directly. Reach Supermemory however fits your workflow: + + + + Official TypeScript and Python SDKs, plus drop-in plugins for the AI SDK, OpenAI, LangChain, and more. + + + Manage memories, search, and scripting from your terminal — it's all `npx supermemory`. + + + Mount a container as a real directory your agent can `ls`, `cat`, and semantically `grep`. + + + Run the full memory engine on your own machine — one binary, zero config, fully offline. + +