Supermemory
State-of-the-art AI agent memory system using ASMR technique that achieved ~99% accuracy on LongMemEval benchmark with multi-agent orchestrated pipeline.
About this tool
Overview
Supermemory introduced a breakthrough technique called ASMR (Agentic Search and Memory Retrieval), which achieved approximately 99% on LongMemEval_s, published on March 22, 2026. This result put them ahead of every publicly benchmarked memory system.
How ASMR Works
Architecture: The system deploys an agent orchestrator utilizing 3 parallel reader (observer) agents powered by Gemini 2.0 Flash, which read through raw sessions concurrently. Their goal is targeted knowledge extraction across six vectors: Personal Information, Preferences, Events, Temporal Data, Updates, and Assistant Info.
Retrieval Approach: When a question arrives, the system does not query a vector database but instead deploys 3 parallel search agents. These agents actively read and reason over stored findings, with specialized focuses: Agent 1 searches for direct facts and explicit statements, while Agent 2 looks for related context, social cues, and implications.
Why It Matters
LongMemEval is designed to simulate real production environments with 115k+ token conversation histories, contradictory information, events spread across multiple sessions, and questions requiring temporal reasoning.
Availability
Supermemory planned to publish and open source everything about this new agent memory system beginning of April 2026.
Pricing
Open-source project.
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