River of TalentMid-size companies were hemorrhaging talent because recruiters simply couldn't keep pace with applicant volume — I found that 95% of candidates went cold within 48 hours of applying, largely because no one could engage them instantly. Recognizing this as both a massive candidate-experience failure and a huge opportunity, I founded River of Talent to build an AI recruiting assistant that never sleeps.
As founder, I owned the full product vision and led design of the conversational AI engine at the core of the platform. I designed a conversational flow capable of triaging and engaging candidates within seconds of their application, then recruited a small technical team to help turn that vision into a working prototype. Beyond the product itself, I pitched the concept to mentors at Founder Institute to stress-test the idea, gather validation, and secure guidance on funding strategy. Once the prototype was built, we ran pilot conversations with real applicants to evaluate response quality and iterated on the model based on that direct feedback.
The results validated the core thesis: in pilot testing, the AI engaged 90% of applicants within 30 seconds, a dramatic improvement over the industry-standard 48-hour lag. This leap in responsiveness directly targeted the candidate drop-off problem that inspired the company in the first place. The impact was recognized externally as well — Founder Institute mentors flagged River of Talent as a top-3 startup in the cohort, citing its potential to meaningfully improve hiring conversion rates industry-wide.
