Enterprise AI Memory
Extend enterprise AI beyond the context window with a persistent memory stack that combines hybrid storage, governed recall, and 74% delta compression.
Beyond Context Windows: True AI Memory
RCTDB v2.0 addresses a core enterprise AI limitation: important context should survive beyond a single prompt or session. The platform keeps useful operational memory available for future workflows without forcing teams to restate everything from scratch.
The memory stack blends semantic, relational, and structured storage so retrieval can remain accurate, explainable, and practical for production systems.
Delta compression reduces storage load by 74% on representative workloads, while the context schema keeps enough structure for governed recall, provenance, and enterprise-grade continuity.
Multi-Layer Memory Architecture
RCTDB v2.0 combines complementary storage paradigms into a single enterprise memory system.
Vector Layer
High-dimensional embedding storage for semantic search and similarity matching across all AI interactions.
Graph Layer
Relationship mapping between entities, concepts, and contexts — enabling complex reasoning chains and knowledge graphs.
SQL Layer
Structured data storage for metadata, configurations, audit trails, and transactional records with ACID compliance.
9D Context Dimensions
Each memory item in RCTDB v2.0 carries 9 structured dimensions — the full RCTDB schema powering identity, sovereignty, payload, social graph, delta compression, SignedAI verification, and evolution.
Identity
Persistent entity identifier and ownership metadata — who owns this memory and which agent created it.
Sovereignty
Data ownership, access rights, and consent flags — enforcing Constitutional AI constraints at the storage layer.
Context
Situational and environmental context — session origin, locale, active agent, and conversation thread.
Payload
The actual content — text, embeddings, structured data, and media references stored in the memory item.
Value
Importance score, decay rate, and retrieval priority — determines how long a memory persists and when it fades.
Social
Relationship graph — links to related memories, parent entities, and cross-agent references for collective recall.
Delta
Change log and versioning — tracks what changed, when, and why, enabling 74% delta compression over raw storage.
Verification
SignedAI attestation scores, consensus level, and trust rating — proof that the memory passed multi-model review.
Evolution
Learning patterns, adaptation history, and feedback loops — how this memory changes and improves over time.