99K deduplicated trades. 61K bills with full text. 940K bill-to-ticker impact mappings. 224M FEC contributions. 3.2M corporate insider events. One 7-layer ML model, one deep-learning Bill Pass Index (AUC 0.74), one stack of LLM behavioral profiles — fused into tiered, labelled signals.
Every congressional stock trade sits at the center of a three-way money flow: donors fund campaigns, committee assignments unlock market-moving information, and trades capture the upside. Each layer is publicly disclosed somewhere — we cross-reference all three so the pattern is unmissable.
Donors · Committees · Trades — three publicly disclosed layers, one cross-referenced map.
Layer 1 · Donors
224M FEC contributions across 5 cycles, mapped to politicians and PACs by 24 industry tags. Plus 2.8M PAC contributions traced back to corporate ownership.
Layer 2 · Committees
3,908 committee assignments cross-referenced with 940K bill-to-ticker impact maps and 17,590 committee meetings. Who has the agenda power and when?
Layer 3 · Trades
99,546 deduplicated STOCK Act disclosures from 354 members, plus 23,408 corporate Form 4 insider events from execs at the same companies.
How it works
From disclosure to signal in three machine-learning passes
Other trackers stop at the trade. We start there — then put every disclosure through a 7-layer weighted scoring model, a deep-learning passage-probability model trained on 37K historical bills, and per-politician LLM behavioral profiles built from 70 features each. You see the insight, not the noise.
Step 01
Congress files a STOCK Act disclosure
Every purchase or sale over $1,000 must be disclosed within 45 days. We ingest all of them in real-time — 99,546 on file. 12,766 were filed late (a violation itself).
e.g. "Pelosi buys NVDA calls · $1M–$5M · filed 38 days after trade"
Step 02
7-layer ML fusion + deep-learning bill passage model
Politician quality (20%) · Herd convergence (20%) · Bill correlation (16%) · Technical context (12%) · Sector momentum (12%) · FEC contribution patterns (10%) · Lobbying alignment (10%). When 3+ layers fire on the same trade, a convergence multiplier (1.3x → 2.0x) amplifies the score. Each ticker also gets a deep-learning Bill Pass Index probability (AUC 0.74, calibrated on 37,132 historical bills with known outcomes).
A Claude Sonnet-trained behavioral profile per politician (70 features each) and per company (iron-triangle map of donors, lobbyists, bills, insiders) explains why the signal fired in plain English. You get tier + direction + convergence + freshness + related bills + 7/30/90-day backtested return — every claim cited to STOCK Act, SEC, FEC, or Congress.gov.
e.g. "STRONG_HERD · BILL_CORRELATED · 7-day lead on markup"
The stack
What's actually under the hood
Most platforms shout "AI" and stop there. Here's the exact data + model stack we run against every congressional disclosure, with row counts and references you can verify.
Layer 1 · Raw federal data
8 direct federal sources, no scrapers
Approved API connections to government data systems — plus licensed market feeds. Refreshed daily, archived forever, fully cited at the row level.
STOCK Act disclosures99,546
Bills (full text, 99.4% pop.)61,601
FEC contributions (5 cycles)224.9M
SEC EDGAR filings indexed391,213
Federal contracts (USASpending)39,408
Daily price bars (FMP+Yahoo)1.94M
Layer 2 · ML models
7-layer weighted fusion + deep-learning Bill Pass Index
Each trade scored across 7 independent intelligence layers; convergence detected when 3+ fire on the same ticker. The Bill Pass Index is a separately-trained probability model, calibrated against 37,132 closed-loop bills (known outcomes).
Claude Sonnet 4.6 profiles every politician on 70 features (donors, sectors, ideology, trading style). Grok 4 maps each company's iron triangle (lobbyists, bill exposure, insider activity). Every claim cited; outputs power the signal narrative and AI chat.
Politician LLM profiles (Sonnet 4.6 v3)2,469
Company LLM profiles (Grok 4 v3)6,151
Bill winners/losers (LLM-derived)6,349
Iron-triangle scores per company0–100
Conflict scores per politician0–100
Layer 4 · Signals + predictions
4 forward-looking engines, deduped to one feed
Outputs from layers 1–3 flow into 4 prediction engines: committee markup (who buys before a markup), pattern (recurring DCA intervals), signal bridge (high-score signals → named tickers), and bill correlation (bill–trade pairings → named tickers).
Disclosures filed late12.8%
Median disclosure gap28 days
Herd convergence detections46
Markup advance-warning window7 days
What the filings show
1 in 8 trades was filed late.
The STOCK Act gives members 45 days to disclose a trade. Across 99,546 deduplicated disclosures, 12,766 missed that deadline. The median trade surfaces 28 days after it happened; the average, 50. That's the window GovGreed is built to close — by showing who filed, what else was happening at the same time, and what the member oversees.
No credit card for the free tier. Founders is locked at $24.50/mo for life — 50% off the post-launch $49 rate. Every paid plan includes everything below it. The ML stack you just read about? You get all of it from Founders up.
Free
$0/mo
No card required · verify the edge before paying
Every page accessible. Today's top 10 signals + top 10 predictions in real time. Enough to know if the stack works for you.
Top 10 A-tier signals + top 10 predictions visible
10 AI chat queries / day (Claude Haiku)
3 watchlist items · sector momentum
Most popular
Founders
$24.50/mo
$24.50 locked forever · 50% off the post-launch $49 rate
The full 4-layer stack: raw federal data, 7-layer ML scoring, LLM behavioral profiles, and forward-looking predictions. Same intelligence funds pay institutional prices for.
Unlimited AI chat · Claude Sonnet 4.6 with full DB access
$100K paper trading portfolio (live Alpaca pricing)
Daily digest email · 8am ET · watchlist only
All future features included — no upsells, ever
Institutional
$975/yr
~$81/mo · billed annually · for trading desks & newsrooms
Everything in Founders, plus the data plumbing — API, webhooks, exports, team seats. Built for funds running quant strategies and newsrooms running investigations.
QuiverQuant ships raw disclosures. Unusual Whales ships options flow. Capitol Trades ships a leaderboard. We ship the ML stack that scores all of it — with cited LLM behavioral profiles on top.
Feature
GovGreed
QuiverQuant
Unusual Whales
Capitol Trades
Congressional trades (STOCK Act)
✓
✓
✓
✓
7-layer weighted ML signal scoring
✓
✗
✗
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Deep-learning Bill Pass Index (AUC 0.74)
✓
✗
✗
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Bill → ticker impact maps (940K)
✓
Partial
✗
✗
LLM behavioral profiles per politician (Sonnet 4.6)
✓
✗
✗
✗
LLM iron-triangle profiles per company (Grok 4)
✓
✗
✗
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FEC contributions (224M rows, 5 cycles)
✓
✗
✗
✗
SEC Form 4 insider events (3.2M cross-refs)
✓
✗
✗
✗
Committee markup alerts (7-day lead)
✓
✗
✗
✗
Cabinet OGE filings + conflict scores
✓
✗
✗
✗
Forward-looking predictions engine (4 sources)
✓
✗
✗
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AI chat with live DB access (cited)
✓
✗
✗
✗
Paper trading portfolio (Alpaca pricing)
✓
✗
✗
✗
Free public tools (no login)
✓
Limited
Limited
Limited
Feeling overwhelmed? That's fair — there are 60+ pages under the hood because every data layer has its own view. You only need 4 of them day-to-day. The 5 steps below get you full value in about 10 minutes.
Onboarding
Your first 10 minutes
Each step saves your progress automatically. You'll get full value in about 10 minutes.
1
Follow 3 politicians we flagged as top-signal
S-tier and A+ tier on our 7-layer signal engine. We picked these based on committee access, trade frequency, and signal score.
2
Watch your sectors of interest
Each sector surfaces every related bill in play, federal contracts flowing to beneficiary tickers, and the Executive Branch officials overseeing it — plus which Congress members have been buying in that space.
3
Enable daily alerts
One email at 8am ET — every new signal, trade, and markup touching your watchlist. Zero noise from things you don't follow. Unsubscribe from your account settings anytime.
4
Place your first paper trade
$100K virtual portfolio via Alpaca live price feeds. Click any A-tier signal → Paper Trade → enter size. Zero risk, real price execution, tracks P&L over time. Good way to verify the signals before going live.
Claude Sonnet with live access to the full intelligence stack. Try: "Which bills would benefit NVDA?" · "Has Pelosi ever traded Lockheed?" · "What's in markup this week and who's been buying in that sector?"
Every plan includes public data. Paid tiers unlock the signal engine, predictions, and AI capacity.
Not financial advice · All data from public federal disclosures (STOCK Act, SEC EDGAR, FEC, USASpending.gov, OGE, Congress.gov) ·
Questions? team@mmamodel.ai
