How to Use Supermemory with AI SDK

Supermemory is presented as a persistent memory layer for AI SDK agents, addressing the framework’s stateless sessions by adding a graph-based memory system, automatically generated user profiles, hybrid retrieval claimed to operate in under 300 milliseconds, and extraction and connector support for sources such as PDFs, audio, Slack, Notion, Drive, and Gmail. The integration is designed to work with AI SDK’s ToolLoopAgent, generateText, and streamText workflows by retrieving relevant context before model calls and storing new memories afterward, without requiring a specific model provider or replacing existing vector databases. The post argues that a memory graph offers relationship tracking, temporal reasoning, contradiction handling, and personalization beyond conventional vector search, and cites benchmark results including 76.7% multi-session accuracy on LongMemEval-S compared with 57.9% for competitors. It also describes security and deployment options including SOC 2 Type 2, HIPAA, GDPR compliance, encryption, self-hosting, VPC, and hybrid deployments, alongside tiered pricing from a free plan to enterprise service. Setup involves installing the Supermemory package, obtaining an API key, and passing its AI SDK tools into an agent or generation loop, with the tools intended to automate memory storage and retrieval.

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