Startup Founders Outreach Platform

A specialized outreach and CRM platform for developers, job seekers, and builders who want to connect with startup founders and early-stage companies. Discover founders, generate AI-powered personalized outreach messages, and track relationships through a comprehensive CRM system.

About

This platform solves a critical problem for technical professionals: finding and connecting with startup founders is fragmented and inefficient. Developers waste time bouncing between scattered communities (Slack groups, email lists, forums) trying to discover interesting startups, and most people don't know how to craft professional outreach messages that get responses.

Our Solution:

Centralized Discovery: Browse hundreds of verified startup founders in one place
AI-Powered Outreach: Generate personalized, high-converting messages using Google Gemini AI
Systematic Tracking: Full CRM tools to manage outreach pipelines across email and LinkedIn

Key Features

🔍 Founder Directory

Advanced Filtering: Filter by contact availability (Apply Link, LinkedIn, Email)
Smart Search: Search across company names, founder names, and descriptions
Flexible Display: Sort by newest, oldest, or alphabetically with 8/25/50 items per page
Rich Information: Company details, founder roles, tech stack, hiring needs, contact info

🤖 AI Outreach Generation

Context-Aware: Powered by Google Gemini 2.5 Flash with PDF resume analysis
Multiple Formats: Email (formal) or LinkedIn (casual) message styles
Three Outreach Types: Job opportunities, collaboration, or networking
Enriched Data: Automatically scrapes company websites and LinkedIn for context
Auto-Save: All generated messages saved for tracking and history

📊 CRM Dashboard

Contact Management: Save and organize founder contacts
Outreach Tracking: See current status of all conversations
Search & Filter: Find contacts by company, name, or keywords
Profile Setup: Upload resume (PDF or text) and set personalization goals
Complete Archive: Searchable history of all generated messages

📋 Kanban Outreach Boards

Dual Pipelines: Separate boards for Email and LinkedIn tracking
Email Stages: Sent → Responded → In Talks → Interviewing → Rejected
LinkedIn Stages: Sent → Responded → Connected → Ghosted
Drag & Drop: Smooth @dnd-kit powered card movement
Auto-Sync: Real-time updates every 30 seconds
Notes Support: Add manual notes for offline conversations

📄 PDF Resume Processing

Client-Side Parsing: Extract text from PDFs using PDF.js
Multimodal AI: Gemini can directly read and analyze PDF resumes
Automatic Context: Resume data automatically enriches AI-generated messages

🔐 Contact Information Gating

Tiered Access: Free users can browse, Pro users access contact details
Smart Paywall: LinkedIn profiles and email addresses behind subscription
Subscription Management: Stripe integration for seamless payments

Use Cases

1. Job Seeker Finding Startup Opportunities

Discover: Browse /opportunities to find early-stage startups hiring
Filter: Use filters to find companies with specific skills or apply links
Save: Click "Save" to add interesting founders to dashboard
Profile Setup: Upload resume and set job search goals
Generate: Create personalized outreach emails with AI
Send: Copy message and send via email or LinkedIn
Track: Drag contact through Kanban stages as conversation progresses
Follow-up: Reference Archive for previous messages

2. Builder Seeking Collaboration

Browse: Find founders working on complementary technologies
Save: Add interesting builders to dashboard
Context: Add projects and collaboration interests to profile
Generate: Create collaboration-focused outreach messages
Connect: Send via LinkedIn for casual peer-to-peer tone
Track: Monitor responses on LinkedIn board
Note: Add manual notes about offline conversations

3. Developer Networking

Discover: Find builders in similar tech spaces
Save: Build network of interesting people
Generate: Create friendly networking messages
Connect: Send casual LinkedIn DMs
Maintain: Keep relationships organized in Connected stage
Engage: Use Archive to remember previous conversations

Technical Architecture

Tech Stack

Frontend:

Next.js 16 (App Router with Turbopack)
React 19.2
TypeScript 5
Tailwind CSS v4
Framer Motion (animations)
@dnd-kit (drag & drop)

Backend & Services:

Firebase Firestore (database)
Firebase Storage (file uploads)
Clerk (authentication)
Google Gemini 2.5 Flash (AI)
Stripe (payments)
PDF.js (document processing)

Development:

ESLint (code quality)
Next.js Turbopack (3x faster builds)
Custom webpack config for PDF.js compatibility

Architecture Highlights

App Router with RSC: Leverages Next.js 15+ App Router with React Server Components for optimal performance and SEO.

Route Protection: Clerk middleware protects routes (/dashboard/*, /opportunities/*, /billing/*, /outreach/*, /admin/*) while keeping landing page public.

Hybrid Rendering: Strategic mix of server-side rendering and client components for best UX.

Real-time Sync: Firestore enables real-time updates across dashboard and outreach boards with 30-second auto-refresh.

Singleton Pattern: Firebase client uses singleton pattern to prevent multiple app instances.

Turbopack Default: Next.js 16 uses Turbopack by default for significantly faster development builds.

Data Model (Firestore Collections)

entry - Directory of startup founders

company, name, role, company_info
linkedinurl, email, company_url, apply_url
published (timestamp), looking_for (tags)

saved_jobs - User's saved contacts

userId, jobId (reference to entry)
savedAt, duplicated job fields for offline access

outreach_records - Generated messages & tracking

ownerUserId, contactId, founderName, company
messageType (email/linkedin), outreachType (job/collaboration/friendship)
generatedMessage, stage, createdAt, updatedAt
linkedinUrl, email for reference

user_profiles - User context for AI generation

resumeText, resumePdfBase64, resumeFilename
goals, name, title, skills, experience, projects
updatedAt

users - Stripe subscription data

stripeCustomerId, subscriptionId, subscriptionStatus
plan (monthly/yearly), expiresAt

Project Structure

startupfoundersdata/
├── app/
│   ├── api/                      # API routes
│   │   ├── generate-outreach/    # AI message generation endpoint
│   │   ├── save-outreach/        # Outreach record persistence
│   │   ├── user-profile/         # Profile management with PDF support
│   │   ├── stripe/               # Payment integration
│   │   │   ├── create-checkout-session/
│   │   │   ├── create-portal-session/
│   │   │   ├── refresh-subscription/
│   │   │   └── webhooks/
│   │   ├── subscription/         # Check subscription status
│   │   └── admin/                # Admin functionality
│   ├── dashboard/                # Saved contacts CRM
│   ├── opportunities/            # Founder directory browser
│   ├── outreach/                 # Kanban boards for tracking
│   ├── billing/                  # Subscription management
│   ├── admin/                    # Admin tools
│   ├── components/               # Shared React components
│   │   ├── Navigation.tsx
│   │   ├── Toast.tsx
│   │   └── [outreach components]
│   ├── layout.tsx                # Root layout with auth
│   ├── page.tsx                  # Landing page
│   └── globals.css               # Global styles
├── lib/
│   ├── firebase/
│   │   ├── clientApp.ts          # Firebase client config
│   │   └── serverApp.ts          # Firebase server config
│   └── utils.ts                  # Utility functions
├── public/
│   └── js/
│       └── pdf.worker.min.js     # PDF.js worker files
├── middleware.ts                 # Clerk authentication middleware
├── next.config.ts                # Next.js configuration
├── tailwind.config.ts            # Tailwind CSS configuration
├── tsconfig.json                 # TypeScript configuration
├── CLAUDE.md                     # Detailed project documentation
└── package.json

Setup & Installation

Prerequisites

Node.js 18+ and npm
Firebase project (Firestore + Storage enabled)
Clerk account for authentication
Google AI API key (Gemini 2.5)
Stripe account (test mode for development)

Environment Variables

Create a .env.local file in the root directory:

# Clerk Authentication
NEXT_PUBLIC_CLERK_PUBLISHABLE_KEY=pk_test_...
CLERK_SECRET_KEY=sk_test_...

# Google AI (Gemini)
GEMINI_API_KEY=...

# Firebase
NEXT_PUBLIC_FIREBASE_API_KEY=...
NEXT_PUBLIC_FIREBASE_AUTH_DOMAIN=your-project.firebaseapp.com
NEXT_PUBLIC_FIREBASE_PROJECT_ID=your-project
NEXT_PUBLIC_FIREBASE_STORAGE_BUCKET=your-project.appspot.com
NEXT_PUBLIC_FIREBASE_MESSAGING_SENDER_ID=...
NEXT_PUBLIC_FIREBASE_APP_ID=...

# Stripe
STRIPE_SECRET_KEY=sk_test_...
STRIPE_PUBLISHABLE_KEY=pk_test_...
STRIPE_WEBHOOK_SECRET=whsec_...

Installation Steps

# Clone the repository
git clone <your-repo-url>
cd startupfoundersdata

# Install dependencies
npm install

# Set up environment variables
cp .env.example .env.local
# Edit .env.local with your credentials

# Run development server with Turbopack (recommended)
npm run dev --turbopack

# Or run standard dev server
npm run dev

# Build for production
npm run build

# Start production server
npm start

# Run linting
npm run lint

The development server will start at http://localhost:3000

Development Guide

Key Commands

npm run dev --turbopack - Start development server with Turbopack (3x faster)
npm run build - Build the application for production
npm run start - Start production server
npm run lint - Run ESLint to check code quality

Working with Firebase

Firestore Schema: Documented in CLAUDE.md - refer to Data Model section above for collection structures.

Client vs Server:

Use lib/firebase/clientApp.ts for browser code
Use lib/firebase/serverApp.ts for API routes and server components
Singleton pattern prevents multiple Firebase app instances

Security Rules: Ensure Firestore security rules allow:

Users to read/write their own data
Public read access to entry collection
Write access to saved_jobs and outreach_records for authenticated users

AI Integration

Gemini API: Located in /app/api/generate-outreach/route.ts

Features:

Multimodal input (can read PDF resumes directly)
Web scraping via jina.ai reader for company context enrichment
Three prompt variations for different outreach types
Configurable tone (formal email vs casual LinkedIn)

Context Building:

User's resume (PDF or text)
User's goals/interests
Founder's company website (scraped)
Founder's LinkedIn profile data (scraped)
Job listing details

PDF Processing

Custom Configuration: Next.js 16 requires special Turbopack config for PDF.js

Worker Files: PDF.js worker files must be in /public/js/pdf.worker.min.js

Usage:

Client-side text extraction from uploaded resumes
Base64 encoding for Firestore storage
Gemini can read PDFs directly for multimodal analysis

Webpack Config: See next.config.ts for canvas aliasing and fallback configuration needed for PDF.js browser compatibility.

Authentication & Authorization

Clerk Setup:

Middleware in middleware.ts protects routes
Protected: /dashboard/*, /opportunities/*, /billing/*, /outreach/*, /admin/*
Public: Landing page (/)

Subscription Checking:

Use useSubscription() hook in client components
Check subscriptionStatus === 'active' for Pro features
Stripe webhook updates subscription status in Firestore

Styling

Tailwind CSS v4:

Uses new @tailwindcss/postcss plugin
CSS variables for theming in globals.css
Dark theme by default

Animations:

Framer Motion for page transitions and interactive elements
Custom animations in tw-animate-css

Key Design Decisions

Why Turbopack?

Next.js 16 uses Turbopack by default, providing up to 3x faster builds compared to webpack in development mode.

Why Firestore?

Real-time synchronization capabilities are essential for CRM features. Firestore's NoSQL structure perfectly fits the flexible contact and outreach data model.

Why Gemini?

Multimodal capabilities allow the AI to directly read PDF resumes, eliminating text extraction errors. Gemini 2.5 Flash offers excellent quality at low cost.

Why Clerk?

Best-in-class authentication with minimal setup. Provides pre-built UI components and comprehensive middleware for route protection.

Why Desktop-only Kanban?

Drag-and-drop UX requires significant screen real estate. Mobile users can still view and update records, but the Kanban board is optimized for desktop workflow.

Why Manual Stage Tracking?

Users manage email and LinkedIn conversations in separate applications. Manual stage updates match the actual workflow better than attempting automated tracking.

Contributing

We welcome contributions! Here's how you can help:

Fork the repository
Create a feature branch: git checkout -b feature/amazing-feature
Commit your changes: git commit -m 'Add amazing feature'
Push to the branch: git push origin feature/amazing-feature
Open a Pull Request

Code Style

Follow existing TypeScript and React patterns
Use Tailwind CSS for styling (no inline styles)
Add comments for complex logic
Run npm run lint before committing

Reporting Issues

Use GitHub Issues to report bugs
Include reproduction steps and environment details
Check existing issues before creating new ones

Documentation

CLAUDE.md: Comprehensive project documentation with architectural details
API Routes: Each API route has inline documentation
Components: Key components have JSDoc comments

License

[Add your license here]

Acknowledgments

Built with:

Next.js - React framework
Firebase - Backend services
Clerk - Authentication
Google AI - Gemini API
Stripe - Payment processing
Tailwind CSS - Styling
Framer Motion - Animations

For detailed technical documentation, see CLAUDE.md

Name		Name	Last commit message	Last commit date
Latest commit History 72 Commits
.cursor/rules		.cursor/rules
.kiro/steering		.kiro/steering
.superdesign/design_iterations		.superdesign/design_iterations
.vscode		.vscode
app		app
components/ui		components/ui
lib		lib
photos		photos
public		public
.gitignore		.gitignore
.windsurfrules		.windsurfrules
@TASK.md		@TASK.md
CLAUDE.md		CLAUDE.md
README.md		README.md
components.json		components.json
eslint.config.mjs		eslint.config.mjs
middleware.ts		middleware.ts
next.config.ts		next.config.ts
package-lock.json		package-lock.json
package.json		package.json
postcss.config.mjs		postcss.config.mjs
tsconfig.json		tsconfig.json

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Startup Founders Outreach Platform

About

Key Features

🔍 Founder Directory

🤖 AI Outreach Generation

📊 CRM Dashboard

📋 Kanban Outreach Boards

📄 PDF Resume Processing

🔐 Contact Information Gating

Use Cases

1. Job Seeker Finding Startup Opportunities

2. Builder Seeking Collaboration

3. Developer Networking

Technical Architecture

Tech Stack

Architecture Highlights

Data Model (Firestore Collections)

Project Structure

Setup & Installation

Prerequisites

Environment Variables

Installation Steps

Development Guide

Key Commands

Working with Firebase

AI Integration

PDF Processing

Authentication & Authorization

Styling

Key Design Decisions

Why Turbopack?

Why Firestore?

Why Gemini?

Why Clerk?

Why Desktop-only Kanban?

Why Manual Stage Tracking?

Contributing

Code Style

Reporting Issues

Documentation

License

Acknowledgments

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