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White Papers

Dual-Signal Retrieval for AI Agent Memory

White Papers

A white paper on ranking an AI agent’s memories by use without making recall worse. A two-year simulation through production code shows why use and correctness must be two separate signals, why every ranking nudge must stay smaller than the gaps it reorders, and why recall and long-term memory need different clocks.

The Hippocampal Index for AI Agents

White Papers

A white paper on why AI agents get slower and costlier the more they remember, and a fix borrowed from the brain: a small index of what the agent knows, kept current by every write and repaired offline. Research, reference design, use cases and an evaluation method.

The Episodic Buffer for AI Agents

White Papers

A white paper on why AI agents lose the middle of long conversations, and a fix borrowed from human memory: a small index of older stretches, each line pointing into the agent’s long-term memory. Research, reference design, use cases and an evaluation method.