What MassSensus Solves and For Whom
For investors, analysts, and market teams that need clearer decision context when sentiment and macro conditions move quickly.
Real-Time AI Crowd Intelligence
for Financial Markets
Crowd-derived market signals powered by AI and real-time behavioral data.
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Crowd Participants
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Macro Data Streams
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Signal Refresh
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CROWD LIVE
Powerful Features for Signal Intelligence
Leverage collective intelligence to improve decision context.
Collective Intelligence
Collective Intelligence
Aggregate insights from thousands of investors to reduce individual bias and improve decision accuracy.
Learn MoreReal-Time Analytics
Real-Time Analytics
Get instant data-driven signals and market insights powered by advanced algorithms and crowd wisdom.
Learn MoreRisk Management
- User A17 09:03-09:08
- User M44 09:19-09:24
- User K08 09:11-09:16
- User T31 09:33-09:38
- User P62 09:26-09:31
Independence-Preserving Design
Anti-Herding Signal Collection
Users submit opinions during randomly assigned 5-minute windows without seeing others.
This prevents social influence and preserves independent thinking, a core requirement for reliable crowd intelligence.
Fees & Rewards
Transparent participation economics designed for clarity and user control.
- Low platform fee applies to signal access.
- A portion is returned to users as asset-based rewards.
- Rewards are based on activity and engagement, not trading performance.
- Full transparency and opt-out options.
How MassSensus Generates Signals
Five-stage pipeline from private input to structured signal output.
1
Private Submission Window
Users are assigned random 5-minute windows to submit views independently, preventing herding.
2
Opinion + Confidence
Users submit direction, conviction, and time horizon.
3
Pseudonymization & Quality Scoring
Inputs are anonymized and weighted based on historical calibration and accuracy.
4
AI Micro-Consumer Simulation
Synthetic AI agents model diverse market behaviors to complement human inputs.
5
Signal Output
Direction, confidence, disagreement level, and key drivers.
Proof and Differentiators
Current evidence is based on transparent methodology and live prototype execution.
- Independent 5-minute submission windows reduce herding during signal collection.
- Pseudonymization and quality-weighting are built into the signal-generation workflow.
- Quant Lab provides a live micro-agent simulation environment with event-level context.
- Production waitlist and referral flows are already running as an early operational outcome.
- External awards and certifications are not currently claimed on this website.
Ready to Join the Revolution?
Get started with calibrated, crowd-powered market signals.
Pseudonymized Data Processing
End-to-End Encryption
Model Audit Logs
Compliance-First Architecture