Ryan Millner co-founded Unwrap.ai and serves as CEO. He runs company strategy, fundraising, and the long-term vision for turning unstructured customer feedback into structured product intelligence. He works across every function, from shaping the product roadmap to closing enterprise deals with teams at Microsoft, lululemon, and GitHub Copilot.
Ryan's path to Unwrap started at Graphiq, a semantic Q+A company that built one of the world's largest knowledge graphs. He spent four years there as Group Product Manager, building technology to ingest data, manage ontologies, and understand natural language queries. When Amazon acquired Graphiq in 2017, Ryan joined the Alexa team as Senior Technical Product Manager. He led the product roadmap for Alexa's semantic NLU/NLP engine and managed a team of 10+ knowledge engineers expanding Alexa's general knowledge capabilities.
After nearly four years at Amazon, Ryan joined the Allen Institute for AI (AI2) incubator as Entrepreneur in Residence. That's where Unwrap took shape. He and co-founder Ashwin Singhania, his colleague from both Graphiq and Amazon, realized the NLP technology they'd spent years building could be pointed at a different problem: customer feedback. The signals were everywhere, spread across support tickets, app reviews, and social media. No product team had the tools to process that volume into structured insight. They built a prototype, tested it with PMs, and left to build Unwrap full-time.
Ryan led Unwrap's $4M seed round in January 2022, launching with a team of four. Within six months, the platform had early adopters including Microsoft, Lyft, Oura, JetBlue, and Perplexity. In February 2025, he closed Unwrap's $12M Series A led by Scale VP, with participation from Atlassian Ventures and strategic investors including Stripe's former CTO David Singleton, Perplexity co-founder Johnny Ho, and HubSpot SVP Karen Ng.
His north star remains the company's founding mission: fill the world with products people love.
It really came through a personal pain point of sitting there, manually reading Reddit, manually going through support tickets, thinking there had to be a better way, and then using this technology that we knew at Alexa to accomplish that task.
AI-powered tools are everywhere, but too often they sacrifice trust, adaptability, and accuracy in the rush to automate. We explore why keeping humans in the loop is the key to driving better outcomes—especially those that apply to understanding and acting on customer feedback.

How keyword-based tools actually work, how clustering-first approaches offer a fundamentally different (and, we argue, better) model, and why this discussion matters for the customer intelligence platform you choose.

Customer analytics tools often come with bold promises. But despite their advanced features and apparent sophistication, the task of uncovering truly actionable insights from your data often still falls back on you.
