Inventory Intelligence

Container Hierarchies

Model any physical or virtual inventory structure. Containers have typed slots, weight limits, count limits, and nested sub-containers — all enforced at the database level.

Typed Slots

Schema-enforced item placement

Define which item types can occupy each slot. A weapon rack only accepts weapons. A reagent pouch only holds consumables. Type violations are rejected before they reach storage.

Per-slot type constraints with allow/deny lists
Maximum stack sizes per item type
Slot-level metadata (position, label, locked state)

Capacity Enforcement

Weight and count limits

Containers enforce maximum weight and item count at every level of the hierarchy. Nested containers contribute their total weight to the parent. Overflow is rejected atomically — no partial insertions.

Recursive weight calculation through nesting
Hard and soft capacity thresholds
Atomic multi-item transactions

Temporal Item Tracking

Every item is a temporal vector. Movements, state changes, and ownership transfers are recorded as observations with full timestamp precision. Query any item's complete history or reconstruct its state at any point in time.

Item Vectors

Items as temporal embeddings

Each item's properties — durability, charge, enchantment level, wear — are encoded as a vector that evolves over time. Semantic search finds items by behavioral similarity, not just by name.

Movement History

Full provenance chain

Track every container transfer, every equip/unequip, every trade. The movement log is append-only and compressed using drift-based segmentation — idle items cost nearly zero storage.

Bulk Operations

Batch transfers and swaps

Move hundreds of items between containers in a single atomic operation. Batch transfers validate all constraints before committing, ensuring consistency across the entire operation.

Audit Replay

Reconstruct the exact state of any container at any historical timestamp. Built on VectorScaleDB's temporal reconstruction engine, audit replay gives you a complete forensic view of inventory changes.

Point-in-Time

Reconstruct any historical state

Query a container's contents as they existed at any timestamp. The reconstruction engine replays compressed segments to rebuild exact item positions, quantities, and properties. No separate audit table required.

Diff View

What changed between two timestamps

Compare container states across any two points in time. See exactly which items were added, removed, modified, or moved. Useful for dispute resolution, rollback analysis, and compliance reporting.

Anomaly Detection

Detect unusual inventory access patterns automatically. VectorScaleDB's behavioral analysis identifies suspicious transfers, impossible item duplication, and abnormal access frequency without manual rule configuration.

Access Patterns

Behavioral baseline monitoring

Each entity's access pattern is tracked as a temporal vector. Sudden changes in access frequency, unusual transfer targets, or atypical item combinations trigger anomaly scores automatically.

No training step — baselines emerge from compression
Per-entity and per-container anomaly scoring
Cross-entity correlation for coordinated anomalies

Integrity Checks

Conservation law enforcement

Items cannot appear from nothing or disappear without a trace. The inventory engine enforces conservation laws — every item has a source and destination. Violations are flagged and logged for investigation.