Building Healthcare Startups: Lessons from Apotigo and Freel

Over the past few years, I've had the privilege of co-founding two startups: Apotigo, a pharmaceutical waste reduction platform, and Freel, an AI-powered portfolio generator. While the industries are different, the entrepreneurial lessons have been remarkably consistent.

Apotigo: Healthcare Meets Sustainability

The Problem We Saw

During my pharmacy internships, I was shocked by the amount of near-expiry medications that were discarded. Perfectly good medicines, sometimes worth thousands of euros, would go to waste because of regulatory constraints and lack of efficient distribution channels.

Our Solution

We built a platform that connected pharmacies with consumers looking for discounted medications. The idea was simple: rescue near-expiry products, offer them at reduced prices, and create a win-win situation.

// Core algorithm for pricing near-expiry products
const calculateDynamicDiscount = (product) => {
  const daysToExpiry = product.expiryDate - new Date();
  const baseDiscount = 0.15; // 15% base discount
  const urgencyMultiplier = Math.max(0, (30 - daysToExpiry) / 30);

  return {
    ...product,
    discountPercentage: Math.min(0.7, baseDiscount + urgencyMultiplier * 0.4),
    finalPrice: product.originalPrice * (1 - discount),
  };
};

What We Learned

1. Regulatory Complexity is Real Healthcare isn't just another market. Every feature we wanted to build had to be evaluated through the lens of pharmaceutical regulations, liability concerns, and professional standards.

2. User Behavior is Hard to Predict We assumed price-conscious consumers would eagerly adopt our platform. Reality? Many people are hesitant to buy discounted medications, even when they're perfectly safe and effective.

3. B2B Sales Cycles Are Long Convincing pharmacies to change their waste management processes took months, not weeks. Each pharmacy had different concerns: liability, workflow integration, profit margins.

The Outcome

While Apotigo didn't reach the scale we envisioned, it taught me invaluable lessons about:

• Market validation
• Regulatory navigation
• The importance of timing in healthcare innovation
• Building trust in sensitive industries

Freel: From Healthcare to AI SaaS

The Pivot to AI

After Apotigo, I wanted to explore how AI could solve different types of problems. The idea for Freel came from a personal pain point: as a freelancer and entrepreneur, I needed to quickly create professional portfolios for different opportunities.

Technical Deep Dive

Freel uses AI to analyze LinkedIn profiles and generate personalized portfolios. Here's a simplified version of our tech stack:

# Portfolio generation pipeline
class PortfolioGenerator:
    def __init__(self):
        self.linkedin_parser = LinkedInParser()
        self.ai_analyzer = AIAnalyzer()
        self.template_engine = TemplateEngine()

    def generate_portfolio(self, linkedin_url):
        # Extract structured data from LinkedIn
        profile_data = self.linkedin_parser.extract(linkedin_url)

        # AI-powered content enhancement
        enhanced_content = self.ai_analyzer.enhance_descriptions(
            profile_data['experiences']
        )

        # Generate responsive portfolio
        portfolio = self.template_engine.render(
            template='modern_professional',
            data=enhanced_content
        )

        return portfolio

Scaling Challenges

Building Freel taught me about:

1. AI Product Development

• Balancing automation with user control
• Managing AI hallucinations and accuracy
• Creating intuitive UX for AI-generated content

2. Full-Stack Responsibility As the solo technical founder, I handled everything:

• React/Next.js frontend
• PostgreSQL database design
• AWS infrastructure
• User authentication and payments

3. Product-Market Fit Metrics We reached ~150 users, which taught me about:

• User onboarding optimization
• Feature prioritization based on usage data
• The difference between interest and adoption

Y Combinator Application: The Learning Experience

Applying to YC W2024 with Freel was educational, even though we weren't accepted.

What We Did Right

• Clear problem statement
• Working product with real users
• Technical co-founder building the solution
• Measurable traction metrics

What We Could Improve

• Market size analysis
• Go-to-market strategy clarity
• Revenue model validation
• Team composition (solo founder challenge)

The Interview Prep Process

# YC Application Framework I Developed

1. **Problem**: What specific pain point are we solving?
2. **Solution**: How does our approach uniquely address this?
3. **Traction**: What evidence do we have of demand?
4. **Market**: How big is the opportunity?
5. **Team**: Why are we the right people to solve this?
6. **Ask**: What do we need to succeed?

Key Lessons Across Both Ventures

1. Start with Users, Not Technology

Both startups taught me that even the coolest technology is useless without real user adoption. Always start with the user problem.

2. Embrace Failure as Data

Apotigo's challenges weren't failures - they were expensive lessons. Each setback provided valuable data for future decisions.

3. Healthcare vs. Tech: Different Rules

Healthcare innovation requires patience, compliance awareness, and deep stakeholder understanding. Tech products can move faster but face different competitive pressures.

4. Solo Founding is Hard

Building Freel alone taught me the importance of co-founders for complementary skills, emotional support, and shared responsibility.

Current Focus and Future Plans

Today, I'm applying these lessons to new opportunities at the intersection of healthcare and AI. The experience with both startups has given me:

• Technical skills in full-stack development and ML
• Domain expertise in healthcare and pharmaceuticals
• Entrepreneurial experience in B2B and B2C markets
• Resilience and adaptability

Advice for Healthcare Entrepreneurs

1. Understand the Regulatory Landscape Early Don't treat compliance as an afterthought. Integrate it into your product design from day one.

2. Build Trust Before Building Features In healthcare, trust is everything. Focus on credibility, transparency, and gradual adoption.

3. Find Healthcare Mentors The industry has unique challenges that only experienced practitioners understand.

4. Be Patient with Sales Cycles Healthcare adoption is measured in months and years, not days and weeks.

Building startups is hard, but incredibly rewarding. If you're working on healthcare innovation or AI products, I'd love to connect and share experiences. Reach out on LinkedIn or email me at aminebenani44@gmail.com!