Best Memory APIs for Building Stateful AI Agents (April 2026)

Memory APIs are presented as infrastructure for giving AI agents persistent state across sessions by storing interactions, extracting facts, maintaining user profiles, and retrieving relevant context, addressing limitations of stateless large language model calls. The comparison evaluates systems using capabilities such as information extraction, multi-session and temporal reasoning, knowledge updates, abstention, latency, graph-based relationship tracking, integrations, self-hosting, and compliance, with LongMemEval cited as a major public benchmark. The source positions Supermemory as a full five-layer context platform, claiming 85.4% LongMemEval accuracy, sub-300ms recall, graph-based memory, broad framework support, and enterprise certifications, while acknowledging its authorship of the product. Mem0 and Zep are characterized as memory-focused alternatives with varying support for profiles, retrieval, and compliance but reported latency and ecosystem gaps, while Letta is described as tightly coupled to its proprietary agent framework. Pinecone and Weaviate are differentiated as vector databases that provide similarity search and storage rather than complete memory systems, requiring teams to separately build or integrate extraction, connectors, profiles, temporal reasoning, and relationship management.

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