#2292 AI Automation that makes cold calls
Timestamps are as accurate as they can be but may be slightly off. We encourage you to listen to the full context.
Podcast Summary
Yevgeniy Matsay was a real estate broker who spent his days making cold calls to expired listing leads, converting only 1-2% of prospects despite hours of daily calling. (03:58) Frustrated with the repetitive nature and low conversion rates, he leveraged his computer science background to build an AI automation that could make these calls for him. The solution worked so well that he got his first listing appointment within the first day of deployment. (05:12) Recognizing the broader market opportunity, he quickly pivoted to selling this as a service to other brokers through Facebook ads, generating $40,000 in revenue within 40 days. (44:12) Today, he and co-founder Aiden Richards are transforming their successful agency model into Rezora, a self-service SaaS platform that enables real estate brokers to deploy AI voice agents for cold calling without technical expertise.
- Main Theme: The evolution from manual cold calling frustrations to AI automation success, demonstrating how industry-specific problems can be solved through technology and scaled from service to SaaS.
Speakers
Yevgeniy Matsay
Yevgeniy is the co-founder and technical lead of Rezora, bringing a unique combination of real estate experience and technical expertise to the company. He graduated with degrees in computer science and cybersecurity before entering real estate, where he spent two years as a successful agent specializing in expired listing leads. His frustration with the repetitive nature of cold calling and his technical background led him to develop AI voice agents that revolutionized his own sales process and eventually became the foundation for Rezora.
Aiden Richards
Aiden Richards is the co-founder of Rezora, responsible for sales, marketing, and operations. He connected with Yevgeniy through Y Combinator's co-founder matching platform and immediately clicked during their first meeting, which lasted for hours. Aiden brings drive, ambition, and business acumen to complement Yevgeniy's technical expertise, handling everything from client relationships to brand building and operational setup.
Key Takeaways
Turn Personal Pain Points Into Business Opportunities
Yevgeniy's frustration with spending 8+ hours daily making cold calls with only 1-2% conversion rates led him to create an AI solution. (03:58) Rather than just solving his own problem, he immediately recognized the broader market opportunity. Within four days of launching Facebook ads, he had his first paying customer, demonstrating how personal industry pain points often represent widespread market needs. This approach works because you deeply understand the problem, the customer, and the existing solutions' limitations.
Start With Agency Model Before Building SaaS
Instead of immediately building complex software, Yevgeniy used tools like Zapier and Vapi to manually create custom AI voice agents for each client. (12:22) This agency approach allowed him to validate market demand, understand customer needs, and generate $40,000 in 40 days while learning what features were truly essential. The manual process revealed that customers wanted extensive customization options, which directly informed the SaaS platform design. This validation-first approach reduces risk and ensures product-market fit before significant development investment.
Focus on Fine-Tuning for Competitive Advantage
While anyone can connect APIs and prompt AI models, Yevgeniy's competitive moat comes from fine-tuning large language models specifically for sales conversations. (16:57) He collects real sales conversations, transcribes them, uses judge LLMs to grade quality, assigns scalar scores, and creates supervised fine-tuning datasets. This process makes the AI agents sound more human and effective at sales, creating a technical barrier that simple prompt-based solutions cannot match.
Choose Co-founders Based on Complementary Skills and Drive
Yevgeniy spent 12+ hours daily coding and realized he needed someone to handle business operations, sales, and marketing. (20:38) Through Y Combinator's co-founder matching platform, he found Aiden, who brought the drive, ambition, and business skills he lacked. Their first meeting lasted hours, and they immediately clicked because Aiden demonstrated the motivation and complementary skills needed. The key was finding someone with equal drive but different expertise, allowing each founder to focus on their strengths.
Leverage AI Tools While Understanding Fundamentals
Yevgeniy emphasizes that tools like Claude Code are powerful but require foundational knowledge to use effectively. (30:19) He compares it to using a hammer - the tool doesn't make you skilled; you need to understand architecture, frameworks, and workflows to know what to ask for and whether the output is good. AI coding tools accelerate development for those who understand the fundamentals but won't replace the need for technical knowledge and proper system design.
Statistics & Facts
- Real estate agents typically achieve only 1-2% conversion rates on cold calls to expired listing leads, despite spending 8+ hours daily making calls. (03:10) Yevgeniy shared this from his personal experience, highlighting the inefficiency that drove him to seek an AI solution.
- The agency achieved an 80% conversion rate from prospects who booked Google Meet calls to paying customers. (10:44) This extremely high conversion rate demonstrated strong product-market fit and effective sales process.
- The team generated $40,000 in revenue within 40 days of launching their Facebook ad campaign, with approximately $34,000 in profit after advertising costs. (44:12)
