A multi-layer intelligence infrastructure designed to transform disconnected hospitality data into institutional-grade market intelligence.
01
DATA
Ingestion
02
SIGNALS
Structuring
03
INTELLIGENCE
Analysis
04
DECISIONS
Decisions
01 / 4
Ingestion Layer
BACCHUS pulls from multiple source types simultaneously — restaurant menus, wine and spirits sales data, pricing telemetry, and geographic signals — normalizing formats and resolving duplicates before they enter the intelligence stack.
Components
Restaurant menus
Pricing telemetry
Alcohol sales datasets
Geographic demand data
Behavioral signals
02 / 4
Entity Layer
Fragmented records are resolved into coherent entities. METEOR deduplicates venues, normalizes item names, and builds the relational graph that makes cross-venue comparison possible at scale.
Components
Duplicate resolution
Name normalization
Location anchoring
Category taxonomy
Relationship mapping
03 / 4
Signal Layer
NEBULA and ECLIPSE combine to produce confidence-weighted, temporally-indexed signals. Each keyword, region, and venue receives a demand score, trend velocity, and pricing interpretation.
Components
Demand scoring (NEBULA)
Trend velocity (ECLIPSE)
Pricing classification
Geographic momentum
Pairing correlations
04 / 4
Decision Layer
QUASAR ranks all derived signals into actionable opportunities, ordered by composite score and confidence. Every output includes explanation, confidence, and recommended action.