I didn’t build MayaMaya because of a single idea—it came from repeatedly seeing the same broken pattern everywhere. The world measures talent incorrectly. Resumes reward storytelling, not real capability. Interviews often reward confidence over competence. Organizations hire for roles, but rarely understand the human behind them. I kept noticing how the same person could be rejected in one place and thrive in another—not because they changed, but because the system never truly understood them. That realization stayed with me: what if we could decode a human beyond a resume? That question became the foundation of MayaMaya. I wanted to build something that looks deeper—into behavior, personality, aptitude, and potential. Inspired by frameworks like Ikigai and principles of behavioral economics, I started thinking about how we could align what someone loves, what they’re good at, what the world needs, and where they can grow—using AI as the engine to make that scalable and actionable. For me, MayaMaya is not just a hiring tool. It’s an attempt to solve something bigger. Why do talented people feel lost? Why do companies struggle to find the right fit? Why is upskilling so random instead of personalized? I wanted to flip the model—understand the human first, then map them to opportunity. At its core, I’m building MayaMaya because I don’t agree with how the world defines talent today. And instead of accepting it, I chose to redesign it.

MayaMaya

Unleash the power of AI-Driven, talent intelligence.

Unleash the power of AI-Driven, talent intelligence.