How much compression does Enterprise AI Memory achieve compared to storing full conversation context?

Enterprise AI Memory achieves 74% lossless delta compression — storing only context changes rather than full snapshots, enabling persistent memory across sessions without exponential storage costs.

How does DelentiaDB differ from vector databases for enterprise AI?

DelentiaDB uses an 8-dimensional schema with governed recall, audit trails, and constitutional constraints. Vector databases provide raw similarity search without governance, explainability, or right-to-erasure controls required for enterprise PDPA compliance.

Does Enterprise AI Memory support PDPA and data sovereignty requirements?

Yes. Enterprise AI Memory includes built-in PDPA Section 33 explainability, right-to-erasure for stored context, role-based access controls, and complete audit trails for all memory read and write operations.

AI Memory

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.

74%

Delta Compression

Memory Layers

Context Dimensions

<50ms

Recall Latency

Beyond Context Windows: True AI Memory

DelentiaDB 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

DelentiaDB 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.

8D Context Dimensions

Each memory item in DelentiaDB v2.0 carries 8 structured dimensions — the full DelentiaDB schema powering identity, sovereignty, payload, social graph, delta compression, and SignedAI verification.

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.

Explore Related Solutions

Hallucination Prevention Dynamic AI Routing