[2603.25097] ElephantBroker: A Knowledge-Grounded Cognitive Runtime for Trustworthy AI Agents

Computer Science > Artificial Intelligence arXiv:2603.25097 (cs) [Submitted on 26 Mar 2026] Title:ElephantBroker: A Knowledge-Grounded Cognitive Runtime for Trustworthy AI Agents Authors:Cristian Lupascu, Alexandru Lupascu View a PDF of the paper titled ElephantBroker: A Knowledge-Grounded Cognitive Runtime for Trustworthy AI Agents, by Cristian Lupascu and 1 other authors View PDF HTML (experimental) Abstract:Large Language Model based agents increasingly operate in high stakes, multi turn settings where factual grounding is critical, yet their memory systems typically rely on flat key value stores or plain vector retrieval with no mechanism to track the provenance or trustworthiness of stored knowledge. We present ElephantBroker, an open source cognitive runtime that unifies a Neo4j knowledge graph with a Qdrant vector store through the Cognee SDK to provide durable, verifiable agent memory. The system implements a complete cognitive loop (store, retrieve, score, compose, protect, learn) comprising a hybrid five source retrieval pipeline, an eleven dimension competitive scoring engine for budget constrained context assembly, a four state evidence verification model, a five stage context lifecycle with goal aware assembly and continuous compaction, a six layer cheap first guard pipeline for safety enforcement, an AI firewall providing enforceable tool call interception and multi tier safety scanning, a nine stage consolidation engine that strengthens useful patterns while...