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A local-first agent memory lifecycle engine: typed memories in an append-only, integrity-chained log with dedupe, conflict detection, forgetting, compaction, verification, query, and portable export.
cogni-mem is a local-first Python framework for typed multi-channel memory, RAG workflows, and memory-aware agent loops — with lifecycle governance and adaptive feedback.
Kazene Trace Receipt Protocol is a minimal standard for recording structured receipts of AI-assisted creation, transformation, routing, and derivative events without storing raw content by default.