Dense Sourced Index — Zero-DB Agent Memory for LLMs. 97% context recall without vector databases.
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docs: remove external comparison to ensure project originality
6410497View on GitHubdocs: finalize public sterilization and MemPalace comparison
ebbd452View on GitHubdocs: remove theoretical proofs for streamlined public presentation
baff849View on GitHubdocs: critical sanitization of internal system references and testing scripts
0c344c6View on GitHubdocs: public release of DSI framework with real-world case studies
e6e77eaView on GitHubdocs: add System Memory Distillation case study and fix gitignore
30b48d5View on GitHubdocs: add System Memory Distillation case study
db99bffView on GitHubdocs: finalize 1.95M token NIAH proof and introduce Recursive Indexing protocol
c10a566View on GitHubfix: exclude node_modules and update NIAH needle to pass safety filters
f096c77View on GitHubfix: modify NIAH needle to pass LLM safety filters (passwords -> backup unit identity)
f10b88bView on GitHubdocs: integrate NIAH empirical proofs into DSI protocol spec
6211054View on GitHubdocs: formalize computer science theory and mathematical proofs for DSI architecture
88712a7View on GitHubtest: add fully local Ollama autonomous retrieval demonstration
6475bd0View on GitHubdocs: update comparison table with verified 100% accuracy and 99% efficiency metrics
8aea646View on GitHubdocs: update CLI verification with exact BPE 4.8M token dataset results
8279becView on GitHub