Measured Response
An enterprise AI Podcast
We team up with enterprise leaders and entrepreneurs to decode the Wild West of enterprise AI, dissecting adoption barriers from ROI and pricing to reliability and risks to reveal what it takes to build AI products that scale.
“Some of the most unpredictable failure modes don’t involve breaking rules at all . They involve exploiting ambiguity in how our policies are interpreted.”
Who we are
Aparna Sinha
Aparna is Senior Vice President at Vercel. She is also a startup investor / advisor at PearVC. Aparna has a track record of successful P&L ownership, creating new revenue streams, building $B+ businesses through technical and go-to-market innovation.
She was previously SVP and Head of Enterprise AI/ML products at Capital One, and prior to that ran Developer Products at Google Cloud leading a 100+ member PM, UX, and DevRel Engineering team responsible for >40 cloud services and open source tools. She was an early contributor to Kubernetes, built the team and grew Google Kubernetes Engine 100x into a Top 3 revenue generator for Cloud. Prior to Cloud Aparna worked on Android, ChromeOS and Play.
Aparna earned a PhD in Electrical Engineering from Stanford. She served as Chair of the Governing Board of the Cloud Native Computing Foundation (CNCF).
Medha Bankhwal
Medha was recently an Associate Partner at QuantumBlack, AI by McKinsey, where she co-founded the firm’s AI Trust practice working in enterprises across sectors including tech, legal, public sector, asset management etc.
She is a member of MLCommons.org (engineering consortium comprising Google, Microsoft, Meta, Nvidia etc.) working on AI Risk & Reliability measurement. Earlier in her career, she co-founded a Google.org-funded EdTech platform for teacher professional development in India, which reached three million educators and was bought by India’s largest telco (Airtel, Bharti Foundation).
Medha holds an MBA from The Wharton School and served as Visiting Lecturer and Senior Fellow for AI and Societal Impact at the School of Development Engineering at the University of California, Berkeley. She has contributed to AI research at McKinsey and others such as Stanford’s 2025 AI Index Report, and MLCommons Agent Product Maturity.
“Our biggest unmet need is orchestration across evaluation, monitoring, and reporting.”