desk-ready review intelligence that combines neural anomaly detection with sentiment propagation modeling to deliver actionable trading signals from consumer data.
Our Neural Core engine transforms raw review data into quantitative intelligence using three components: embeddings, anomaly detection, and incremental statistics.
The Echo Engine models how consumer sentiment cascades across related locations and competing brands, turning a single signal into a market-wide view.
The public product focuses on the monitored universe with real current data. Today that means 79 actively monitored chains and 309K+ reviews from 21K+ locations with review coverage, across restaurants, retail, grocery, and pharmacy.
A four-stage pipeline transforms millions of consumer reviews into actionable intelligence for investment teams.
Automated scrapers pull public consumer reviews into the live dataset, then normalize, deduplicate, and quality-score them before storage and downstream analysis.
Neural Core processes each review through 384-dim embeddings, extracting sentiment, topics, and semantic meaning far beyond star ratings.
Isolation Forest flags statistical anomalies: unusual rating drops, sentiment shifts, and review volume spikes that deviate from historical baselines.
Echo Engine propagates detected anomalies across geographic and brand networks, generating scored trading signals with directional context.
Most alternative data providers sell raw exhaust and leave the desk to normalize it. ReviewSignal focuses on monitored signals, visible operating context, and delivery surfaces that a PM or analyst can actually use.
Detect consumer sentiment shifts before they surface in earnings reports.