
supermemory™
Universal memory API for AI apps that gives LLMs long-term context and handles retrieval, so developers skip building their own RAG pipeline.

Universal memory API for AI apps that gives LLMs long-term context and handles retrieval, so developers skip building their own RAG pipeline.
Universal memory API for AI apps that gives LLMs long-term context and handles retrieval, so developers skip building their own RAG pipeline.
Giving an LLM app a memory that lasts beyond one conversation is the job supermemory handles. It is a memory API for AI developers that stores context across sessions, so your app can personalize answers without you building retrieval from scratch.
Supermemory connects to existing sources such as Notion, Google Drive and CRMs, and it works with any model provider, so you are not tied to one vendor.
The pitch centers on speed and scale.
Supermemory claims sub-400ms latency, a reworked approach to RAG, and room for billions of data points.
It also covers the usual headaches of retrieval projects: slow or costly vector databases, embedding model choices, file parsing, sync failures and multimodal content.
SDKs for Python and JavaScript are available, and the team says deployment takes days rather than months.
Data can live in the cloud, on-prem or on-device, which matters if compliance limits where information may be stored.
Pricing is enterprise, so expect to talk to the team rather than sign up on a pricing page.
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enterprise
https://supermemory.ai/
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