Intratalent

Intratalent is an AI-powered recruiting engine that revolutionizes hiring by eliminating bias, accelerating screening, and streamlining the vetting process—all while integrating seamlessly with 35+ Applicant Tracking Systems (ATS). Traditional hiring is slow, manual, and prone to human bias. Recruiters either manually sift through thousands of resumes or rely on keyword filters that overlook top talent. Our screening platform instantly analyzes resumes, GitHub code, and research papers, providing transparent, AI-driven rankings in seconds and allowing non-technical recruiters to confidently evaluate technical candidates. Beyond screening, we tackle the most overlooked hiring bottleneck: reference checks. Our AI-powered vetting platform autonomously identifies, contacts, and analyzes references, eliminating the reliance on self-reported recommendations. Using LLMs, embedding models, and AI-driven outreach, we find credible third-party references, contact them through automated messaging and calls, and assess responses using sentiment analysis and linguistic credibility scoring. This end-to-end, AI-driven vetting ensures that companies hire not just the best applicants on paper—but the best applicants in reality. With a 1-minute onboarding time, seamless ATS integrations, and scalable automation, Intratalent is set to become the default infrastructure for inbound hiring and reference validation.

Intratalent was founded by a couple of best friends at Stanford who have built and scaled AI-driven solutions across multiple industries. Their team has deep expertise in LLMs, embeddings, and AI-powered automation, with experience spanning HR tech, finance, and enterprise AI systems. They’ve collaborated on high-impact AI projects together, developing production-grade AI products in record time. Rishi Sadanandan leads product, growth, and strategy, leveraging his experience in AI-powered HR tech and finance from L3Harris to drive scalable execution. Soham Vasanawala specializes in LLM fine-tuning and AI search architectures, with research experience at Stanford’s Magnetic Resonance Systems Lab and past work in AI-powered hiring and fitness platforms. Jay Khemchandani, an AI and NLP expert, won the Grand Prize at TreeHacks for his computer vision and NLP-powered robot. He has also developed RAG+AI automation tools for real estate and enterprise, which are still in use today. They are a team of builders and problem-solvers, committed to eliminating bias, streamlining hiring, and transforming talent acquisition through AI. Our deep technical background, fast execution, and proven ability to deliver scalable AI solutions make us uniquely positioned to redefine how companies find and vet top talent.