Governed Knowledge Bundles: Verified Persistent Memory for Stateless Language Models

Large language models are fundamentally stateless, creating a critical gap for applications requiring long-term operational continuity. We present Governed Knowledge Bundles (GKB), an architecture that treats persistent memory as a governance problem — where the challenge is not recall, but verified consistency, integrity preservation, and recoverable state. GKB organizes knowledge into domain-separated, hash-verified, append-only bundles with explicit invariant/variable layer separation, boot-time integrity verification, canonical terminology enforcement, and structured consolidation protocols. Evaluated across two distinct platforms over four months, GKB achieves 95–100% terminology fidelity, 96.4% state recall accuracy, and 0.971 identity continuity index across cold starts. Note: The architecture described in this work is the subject of a patent application (OEPM, filed 25 March 2026). This publication is freely available for academic and individual research use. For commercial licensing inquiries, contact the author.https://www.linkedin.com/in/andcardo/