diff --git a/apps/docs/intro.mdx b/apps/docs/intro.mdx index 1aba978e..861f1600 100644 --- a/apps/docs/intro.mdx +++ b/apps/docs/intro.mdx @@ -6,8 +6,7 @@ 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. -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: - +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) @@ -28,7 +27,6 @@ All this, coming together, makes supermemory the best abstraction to provide to #### Ingestion and Extraction Supermemory handles all the extraction, for [any data type that you have](/concepts/content-types). - - Text - Conversations - Files (PDF, Images, Docs) @@ -43,7 +41,6 @@ We offer three ways to add context to your LLMs: ![memory graph](/images/memory-graph.png) Supermemory learns and builds the memory for the user. These are extracted facts about the user, 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. @@ -63,16 +60,17 @@ This leads to a much better retrieval system, and extremely personalized respons #### 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 - Contextual chunking - Works well with the memory engine -See the full API Reference tab for detailed endpoint documentation. + + See the full API Reference tab for detailed endpoint documentation. + + - 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`). You can mix and match based on your needs. ## Next steps