Building AI Startups

Learn how to build and deploy AI agents that actually work in production. From understanding agent architectures to implementing them with proper data infrastructure, we'll cover practical approaches that founders can use immediately.

• •Designing dependable AI agents for real-world use cases
• •Data collection, structuring, and management strategies
• •Building scalable data infrastructure investors look for
• •Context engineering and agent-data integration

Discover how to position your AI startup for investment. Learn what makes AI companies fundable and how to communicate your technical advantages to investors.

• •What investors look for in AI startups
• •Communicating technical moats and AI differentiation
• •Using AI tools for investor research

This series is designed for founders building AI companies, technical co-founders exploring AI opportunities, and entrepreneurs looking to understand how to position AI startups for investment.

Founder & CEO, Platvix

Aqib Zeeshan is the founder of Platvix, building investment intelligence that revolutionizes how startups connect with VCs, angels, and PE firms. With 7+ years building AI agents, fine-tuning ML models, and developing enterprise applications, he's now applying this expertise to solve critical fundraising challenges, creating AI systems that evaluate startups, match them with investors, and streamline capital raising.

Platvix combines technical AI capabilities with investment insights, helping founders navigate the VC and PE landscape more effectively. From automating investor research to intelligent matching algorithms, Zeeshan focuses on building reliable super agents that work in real-world fundraising scenarios, not just technical demos.

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