Venturely
A market intelligence platform that helps investors and founders research more than 20,000 startups and follow funding, leadership, and company signals.
React 19 · Express 5 · PostgreSQL · Puppeteer Stealth · Socket.io · Paystack · Cheerio · JSDOM · Node-cron · JWT · Tailwind CSS
Live Platform
01 Product overview
What the product does
Venturely is an ecosystem of intelligence products designed for investors, startup founders, CTOs, and anyone who needs accurate, real-time data on the global startup landscape. The platform aggregates and analyzes information on over 20,000 startups, providing workspace tools for research and a proprietary signal engine that uses AI to detect events like funding rounds, company distress, cofounder disagreements, and market shifts before they surface in mainstream reporting.
02 Problem and context
What it needed to solve
The startup data market is fragmented, expensive, and slow. By the time a funding round makes headlines, the opportunity has already closed. Investors and founders need intelligence that moves ahead of the news cycle, not behind it. Venturely solves this by building a signal layer on top of comprehensive startup data, turning noise into actionable intelligence.
03 My contribution
What I worked on
- Cofounded the product and built its application, data workflows, and production systems
- Designed and implemented the full system architecture from database schema to production deployment
- Built the AI-powered scraping pipeline that collects and normalizes startup data at scale
- Developed the workspace features: briefs, dossiers, watchlists, signals, saved startups, and team collaboration
- Implemented the subscription and billing system with Paystack integration and multi-currency support
- Built real-time features with Socket.io for collaborative workspace updates
05 Engineering and outcomes
Implementation details
System
- React 19 frontend with modular workspace architecture and responsive design
- Express 5 REST API with JWT authentication, OTP verification, and role-based access control
- PostgreSQL database with complex relational models for startups, users, workspaces, and signals
- AI scraping pipeline using Puppeteer Stealth, Cheerio, and JSDOM for data extraction and normalization
- Node-cron scheduled jobs for continuous data refresh and signal detection
- Socket.io for real-time workspace collaboration and notification delivery
- Tiered subscription model with Paystack payment processing and webhook handling
Verified results
- 20,000+ StartupsIndexed and tracked with structured data covering funding, team, market, and operational metrics.
- Signal EngineAI-powered detection system that flags funding rounds, bankruptcies, layoffs, and leadership changes before mainstream coverage.
- Workspace EcosystemFull research toolkit: briefs, dossiers, watchlists, signals, saved entities, team collaboration, and notes.
Lessons
- Data quality compounds. A well-structured scraping pipeline saves months of manual cleanup downstream.
- Subscription billing is deceptively complex. Multi-currency, webhooks, and edge cases (failed payments, upgrades mid-cycle) need to be designed upfront.
- Real-time collaboration requires careful state management. Socket.io event architecture needs to be as well-planned as the REST API.