Sentinel-Alpha is a four-layer AI market intelligence engine that monitors real-time social signals, institutional data, and market internals to answer one question: why are markets moving?
Rather than reacting to price action after the fact, Sentinel-Alpha detects emerging market narratives early, tracks their lifecycle, assesses crowd psychology, and grades its own predictions over time — creating a self-improving analytical system.
The engine runs autonomously on every trading day. Full market scans occur hourly during market hours (9:30 AM – 4:00 PM ET), with deep psychological analyses at three key moments: pre-market (8:00 AM), midday (12:30 PM), and post-close (4:15 PM). Data on this page refreshes automatically every 15 minutes.
The sentiment gauge reflects Sentinel-Alpha's current read on market psychology, scored from -1.0 (extreme fear) to +1.0 (extreme greed). This isn't just a price-based indicator — it synthesizes narrative tone, crowd positioning, and institutional signals into a single score.
The assessment text explains the key factors driving the current score. Consensus strength measures how unified market participants are — high consensus (above 70%) can itself be a contrarian warning signal.
These are the top 5 market-moving stories right now, ranked by strength and relevance. Each narrative represents a cluster of related signals — news reports, social posts, analyst commentary, and data releases — that Sentinel-Alpha has identified as driving market behavior.
Expand any narrative to see its full summary, sentiment breakdown, and related tickers. Each narrative is assigned a temporal tier:
Sentinel-Alpha's flagship analytical output — a detailed written analysis produced three times daily by the system's deepest reasoning layer. The synopsis goes beyond what the data says on the surface to examine what the crowd believes, what the crowd may be missing, and where the asymmetric opportunities lie.
Each synopsis is timestamped and labeled with its analysis type (pre-market, midday, or post-close) so you know the context in which it was written.
Sentinel-Alpha generates predicted market moves across all three temporal tiers. Each prediction includes a direction (Bullish, Bearish, Neutral, or Volatile), estimated magnitude, timeframe, confidence level, and the key catalyst driving the call. The range of outcomes section shows best, base, and worst case scenarios with probability estimates.
Predictions are refreshed three times daily during deep analysis cycles and carried forward between updates.
Early warning signals that fire when Sentinel-Alpha detects conditions historically associated with market reversals or surprises. This section is intentionally hidden when no alerts are active — if you see it, pay attention. There are four alert types:
Each alert carries a severity level (low, medium, high, critical) and lists the specific tickers most exposed.
Seeds are the earliest detectable signals of emerging market narratives — ideas, themes, or catalysts that haven't yet reached mainstream consensus. Think of them as narrative intelligence gathered before it becomes a headline.
Every seed progresses through a lifecycle:
Conviction (1–10) measures how strongly the evidence supports a seed. Velocity tracks whether conviction is rising or falling. Seeds in the Consensus stage are a warning — narratives that everyone agrees on often precede reversals. Seeds with no new evidence for 5+ cycles are automatically killed.
Sentinel-Alpha grades its own predictions against actual market outcomes. The dashboard shows trailing 30-day performance across five dimensions: directional accuracy (did the market move the right way?), narrative accuracy (was the reason correct?), calibration score (are confidence levels honest?), seeds confirmed (how many early calls were validated?), and average foresight (how early were seeds detected?).
The calibration chart breaks this down by confidence bucket. Bars above the target line suggest the system is underconfident; bars below suggest overconfidence. Performance data builds over time — expect this section to be sparse in the system's first days of operation.
Atoms are the smallest unit of market information in the system — a single signal captured from social media, news, or market data. Atoms are the raw material that gets processed into narratives and seeds.
Temporal Tiers classify every narrative, seed, and prediction by time horizon. Tier 3 is hours-to-days, Tier 2 is days-to-weeks, Tier 1 is weeks-to-months. This separates daily noise from structural market shifts.
Self-Grading Loop — Sentinel-Alpha doesn't just make predictions, it grades them against actual outcomes and calibrates itself over time. If the system is consistently overconfident in one area, it automatically dampens its confidence. This creates an engine that improves with every trading day.
Sentinel-Alpha has not yet produced its first psychological analysis. This section will populate after the first Opus cycle runs during market hours.
| ID ▼ | Thesis ▼ | Stage ▼ | Tier ▼ | Conviction ▼ | Velocity ▼ | ||
|---|---|---|---|---|---|---|---|
| No seeds detected yet. Seeds will appear as narratives emerge. | |||||||