SEC Event Intelligence Platform
See what's coming
"You see things; and you say, 'Why?' But I dream things that never were; and I say, 'Why not?'"
- George Bernard Shaw
"There is one thing stronger than all the armies in the world, and that is an idea whose time has come."
- Victor Hugo
For hedge funds and asset managers. Initial release focuses on data delivery and risk management - immediate customer value with straightforward sales motion.
Events extracted within minutes of SEC filing
vs hours/days for competitors
30 event types with magnitude, timing
and strategic importance scoring
Risk alerts with quantified impact
-8% to -30% average historical returns
The problems we solve for financial professionals
Event Engine
Structured JSON feeds of SEC events
Real-time delivery via REST API with structured JSON responses
| Ticker | Company | Event Type | Event Date | Filing Date |
|---|---|---|---|---|
| WLK | Westlake Corp | investigated_regulatory_probe | 2024-10-01 | 2025-10-31 |
| OBK | Origin Bancorp | restated_accounting_correction | 2025-10-31 | 2025-10-31 |
| ETR | Entergy Corp | investigated_sec_investigation | 2024-12-01 | 2025-10-31 |
| D | Dominion Energy | restated_financial_restatement | 2025-10-31 | 2025-10-31 |
| CLF | Cleveland-Cliffs | material_weakness_identified | 2025-10-31 | 2025-10-31 |
Risk monitoring, short-selling signals, compliance tracking, portfolio risk management
Event-driven strategies, growth catalysts, innovation milestones, partnership signals for momentum
Competitive intelligence, sector analysis, benchmark tracking
Event Engine
Rule-based event pattern matching for stock predictions
Example Pattern: Management action during distress = +94% recovery (Contrarian Rebound)
Extract all high-value events 30 days before each SEC filing. Create event signature (count, types, sentiment, IDF scores).
Measure stock performance 1, 3, 6, and 9 months after each filing. Classify into performance buckets.
Group filings by performance bucket. Find common event patterns using association rule mining.
Create IF-THEN rules: "IF pattern X (CEO + refinancing) THEN expect +125% with Z% confidence"
Extract event signature → Match to patterns → Predict performance without ML models!
Rule-based only
Instant predictions
Interpretable rules
V9 Intelligence
Multi-dimensional company health assessment
Quality of recent SEC filing events (90-day window)
Financial quality and valuation metrics
Special situations and market regime detection
3-month predicted return (percentile-ranked)
Model reliability and data quality
Weighted combination of all dimensions
How teams use scoring intelligence
Screen potential investments using event-driven signals. Identify companies with positive catalysts before they're priced in.
Track SEC investigations, material weaknesses, and regulatory probes. Monitor litigation risk and compliance issues across portfolios.
Benchmark against peers, track competitor filings, and understand market perception through event analysis.
Real-time alerts on red-flag events. Portfolio-wide monitoring for distress signals, restatements, and governance issues.
Build alpha factors from structured event data. Backtest event-driven strategies with historical impact analysis.
Track sector trends, M&A activity, and strategic moves. Monitor competitor filings for early signals.
V9 Intelligence
Q2 2026 - XGBoost meta-learning system
XGBoost model predicts 3-month stock returns with 0.1518 correlation (professional quant fund level)
Top 3.7% of the 2,117-company universe. These companies combine excellent SEC event signals, strong fundamentals, and favorable market positioning.
| Rank | Ticker | Overall Score | Event | Fundamental | Predicted Return | Confidence |
|---|---|---|---|---|---|---|
| 1 | RXN | 94/100 | 99 | 86 | +21.9% | 78% |
| 2 | FHI | 90/100 | 100 | 100 | +6.4% | 93% |
| 3 | ATEN | 87/100 | 95 | 92 | +8.9% | 93% |
| 4 | LOGI | 87/100 | 84 | 98 | +9.7% | 93% |
| 5 | FTDR | 86/100 | 91 | 98 | +6.3% | 93% |
Ask questions in plain English
The Innovation: AI generates structured intent (not unreliable SQL) - we query multiple data sources - AI synthesizes actionable insights
Claude Sonnet understands user question semantically
Queries all relevant data sources in parallel
Matches events to stock data by CIK/ticker/date
Claude Sonnet generates narrative insights
Executive-ready output with citations
With 19 data sources, the possibilities are endless. Here are just a few examples:
"Show me companies that defaulted in 2024 and their stock performance"
"Which executives sold stock before earnings misses?"
"Find companies with rising debt and declining revenue"
"Show M&A deals where target stock rose before announcement"
Demo Query Result: "75% of defaulting companies showed warning signs 30 days before announcement with an average stock decline of -17.4%"
Find stocks with interesting price movements
Stocks that plummeted >15% in a single day. Find sell-offs, bad news reactions, or market panics.
Example: FVTI dropped 85% on Oct 11, 2024
Stocks that surged >15% in one day. Acquisitions, FDA approvals, breakthrough products.
Example: EFSH spiked 199% on Oct 18, 2024
Stocks that dropped hard but bounced back fast. Oversold reversals, market over-reactions.
Example: TWOU recovered 75% in just 2 days
Fast SQL queries on 15M daily price records. Self-joins to calculate day-over-day changes.
Filter by movement type, threshold (>15%), price range ($1+), and volume (>10K).
Sort by magnitude. Get the most dramatic drops and spikes first.
Get 30 days before/after for detailed analysis of each movement.
Query Speed
Real Data
Historical Coverage
Large addressable market with clear customer segments
TAM
Financial Data & Analytics
SAM
Alternative Data & AI Analytics
SOM
SEC-focused Intelligence Tools
Click any segment to see targeting strategy →
Event-driven strategies, short selling, alpha generation
~3,500 firms
Risk monitoring, portfolio screening, due diligence
~5,000 firms
Client portfolio monitoring, risk alerts, research
~15,000 firms
M&A research, compliance, deal sourcing
~500 firms
Securities litigation, regulatory research
~2,000 firms
Donor screening, foundation research, due diligence
~8,000 orgs
Exploring the next frontier of SEC intelligence
10-20 years historical data for better rare event detection
Proprietary SEC table extraction for competitive edge
Predict IPO performance from S-1 filings
Q1 2026 - Major upgrade with 10-20 years historical data
V8 Baseline: 0.25 correlation, F1 0.64 on 45K samples (3 years). V11 targets 0.28-0.32 correlation (+12-28%) with 10x more training data.
Q3 2026 - Proprietary SEC table extraction
Competitive Edge: Proprietary data not available in FMP, Bloomberg, or FactSet APIs. Forward-looking indicators that predict performance before it shows in standard financials.
Predict IPO performance - client-requested research
Client Request: Getting asked about IPO modeling capability. Early-stage feasibility study in progress.