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UC Berkeley Dropouts Raise $28M for AI Marketing Automation

Conversion, an AI-driven marketing automation startup founded by two UC Berkeley dropouts, just raised a $28 million Series A led by Abstract. The founders built the product by hacking HubSpot, conducted 160 customer interviews, and dropped out to bootstrap growth. Now nearing $10M ARR with 90% mid-market adoption, Conversion targets businesses replacing legacy tools with its baked-in AI features.

Published July 30, 2025 at 12:09 PM EDT in Artificial Intelligence (AI)

AI Marketing Startup Conversion Secures $28M Series A

Conversion, the AI-powered marketing automation platform founded five years ago by UC Berkeley dropouts Neil Tewari and James Jiao, has announced a $28 million Series A led by Abstract, with participation from True Ventures and HOF Capital.

From High School Prank to First Investment

Tewari’s journey began in high school when he was caught watching a TechCrunch Disrupt livestream in class. Too embarrassed to call his parents, he rang a family friend instead—and four years later that same friend became Conversion’s first investor.

Hacking HubSpot to Build the Product

While roommates at Berkeley, Tewari and Jiao added custom automation features to their HubSpot account for internal use. After 160 customer discovery interviews with marketing VPs at mid-size companies, they raised a $2 million seed round and dropped out at 19, living frugally in a crowded apartment.

AI at the Core of Automation

With ChatGPT’s arrival, Conversion baked AI into its core, automating lead organization and crafting personalized follow-up emails. The startup is now approaching $10 million ARR, with 90% of its customers replacing legacy tools with Conversion’s native AI capabilities.

Standing Out in a Crowded Market

  • Legacy giants: HubSpot
  • Adobe Marketo
  • Salesforce Pardot
  • AI natives: Jasper
  • Writer AI
  • Iterable
  • Copy.ai

Rather than chasing first-time tool buyers, Conversion is laser-focused on mid-market teams looking to replace outdated platforms. Their strategy of targeting existing users of legacy automation tools underscores a classic Silicon Valley playbook: solve a real pain, scale fast, and let AI adoption drive the next phase of growth.

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