Executive Summary
Cloud Einsteins designed and built ScanEdge AI, a fully serverless options flow intelligence platform that scans institutional trading activity in real time and delivers actionable trade signals to retail traders. The platform processes over 1,600 options trades per session through a proprietary 7-layer AI analysis system, runs 7 automated daily scans, and serves subscribers through a complete web application with an AI copilot, trade journal, performance analytics, and multi-channel alert delivery.
The entire platform runs on AWS with zero servers to manage and scales to support thousands of concurrent users while maintaining an estimated 97% gross margin.
The Challenge
Retail options traders face a fundamental information gap. Institutional investors have access to sophisticated tools that track unusual options activity, detect insider buying patterns, and analyze market sentiment in real time. These tools typically cost $150 to $500 per month and require significant expertise to interpret.
ScanEdge AI needed a platform that could:
- Ingest 1,600+ institutional trades per session and apply multi-layer analysis in real time
- Deliver specific contract recommendations with entry, target, and stop plans
- Run 7 automated scans daily across market sessions
- Provide an AI copilot for on-demand trading intelligence
- Handle subscription billing with tiered access controls
- Scale to thousands of concurrent users without infrastructure overhead
The Solution
Cloud Einsteins architected and built the entire platform on AWS using a fully serverless approach. The system combines real-time data ingestion, a proprietary 7-layer AI analysis engine, automated scheduling, multi-channel alerting, and a 21-page web application with authentication, billing, and an AI trading assistant powered by Amazon Bedrock.
Architecture
Delivery Scope
Cloud Einsteins owned the full product lifecycle: architecture design, backend development (Python 3.11 on Lambda), API layer (25+ endpoints via API Gateway), AI copilot integration (Amazon Bedrock), front-end application (21-page Next.js on S3/CloudFront), user authentication (Cognito), multi-channel alerting (SES and SNS), automated scheduling (EventBridge), and security hardening (WAF). The platform was delivered as a production-ready SaaS product with zero servers to manage.
AWS Services Used
The 7-Layer Analysis Engine
Every trade signal passes through a proprietary 7-layer analysis pipeline before reaching subscribers. This multi-stage approach filters noise, validates quality, and confirms signals against real-time market conditions.
| Layer | Function |
|---|---|
| 1. Flow Detection | Scans 1,600+ institutional options trades per session for unusual activity |
| 2. Quality Filtering | Filters for $50K+ premium, 68%+ bullish sentiment, 2+ alerts, and 14-60 DTE |
| 3. Technical Confirmation | Validates against SMA, RSI, support/resistance levels, and 3-month volume history |
| 4. Risk Screening | Checks for upcoming earnings, SPY correlation, SEC filings, and press releases |
| 5. Insider Detection | Cross-references SEC Form 4 filings within a 14-day window |
| 6. Affordability Classification | Classifies each signal as an Options Play or Stock Play based on account size |
| 7. Live Confirmation | Issues GO or ABORT at 10:15 AM ET based on live price action after market open |
Key Metrics
Business Impact
- Fully operational SaaS product delivered from concept to production on AWS
- Zero-server architecture that scales automatically with subscriber growth
- Real-time institutional trade analysis with 7-layer signal validation
- Multi-channel delivery through web app, email (SES), and SMS (SNS)
- AI copilot (EdgeIQ) powered by Amazon Bedrock for on-demand trading intelligence
- Complete subscriber experience with authentication, billing, trade journal, and performance analytics
- Architecture designed to maintain 97%+ gross margin at scale
Cloud Einsteins Role
Cloud Einsteins owned the entire product lifecycle from concept through production launch: product architecture, AI engine design and development, full-stack web application build, API layer development, authentication and billing integration, multi-channel alerting, automated scheduling, and security hardening. This was not an infrastructure deployment. It was a complete product build delivered as a production-ready SaaS platform.
Ideal Buyer Fit
Organizations that need to build a data-intensive, AI-powered product on AWS from the ground up. Applicable to FinTech, HealthTech, GovTech, and any domain requiring real-time data processing, multi-layer analysis, and subscriber-facing SaaS delivery. This engagement model demonstrates Cloud Einsteins' ability to serve as a full product development partner, not just an infrastructure provider.