SynFlow — Enterprise Intelligence Platform

Problem

Private deal networks rely on manual introductions and spreadsheets. Matching the right profile to the right deal is slow, subjective, and misses opportunities.

Business Impact

Deal networks lose millions in missed connections because matching is manual. SynFlow automates profile-to-deal matching with scoring algorithms, reducing time-to-introduction from days to seconds.

System Approach

• Spring Boot 3.4 + Java 21 REST API with JWT authentication and Spring Security
• Next.js 14 App Router frontend with TypeScript, React Query, and React Hook Form
• PostgreSQL 16 for relational data with Flyway migrations
• Redis 7 for session caching and rate limiting
• OpenAI GPT-4o integration for AI-powered profile generation from raw text
• D3.js and Recharts for dashboard visualizations and analytics
• AES-256 encryption for sensitive profile and deal data

Key Decisions & Trade-offs

• Rule-based scoring over pure ML — explainable matches matter more than black-box predictions in deal networks
• REAL and SHADOW profile types — supports both verified and anonymous introductions
• Next.js 14 over SPA — better SEO for public-facing profile pages, server components for performance
• AES-256 field-level encryption — sensitive deal data encrypted at rest, not just in transit

Current Status

Full-stack application functional. Profile management, deal tracking, intelligence matching, AI profile generator, dashboard, and admin panel all working.

Roadmap

• Add real-time notifications for new deal matches
• Implement graph-based relationship mapping between profiles
• Add deal pipeline analytics with conversion tracking

What I'd Improve Next

• Could add vector search for semantic profile matching
• Consider adding email digest for weekly match summaries

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