Oracle Agent Memory: Database-Native Substrate for Long-Horizon AI Agents
This arXiv paper introduces Oracle Agent Memory, a system designed to handle the complexity of retaining and managing state for long-horizon AI agents. Rather than relying solely on document retrieval, the architecture treats memory as a lifecycle involving ingestion, extraction, consolidation, and revision. It leverages Oracle Database to provide durable, scoped, and retrievable state that persists across sessions and conversations.
Moves beyond simple RAG by treating agent memory as a structured, durable lifecycle problem.