Ryan Strong

ROVR is a proprietary robot that uses patented technologies to collect live inventory data for in-store retailers. This data is used to satisfy audits and optimize supply chain logistics with third-party distributors. I led a team of product managers, UX designers, market researchers, and QA to design a product that is near the cheapest in the market and has the least amount of impact on the consumer shopping experience of any competitor.

My teams improved the customer’s in-store shopping experience for the cashier-less project by removing the cashier and all physical self-checkout stations from the checkout process. I oversaw the product design, go-to-market strategy, development, and initial launch.

For this project, I managed the redesign of the 7Eleven delivery app, 7NOW. I oversaw the initial market research and testing that led to the redesign business case through the app design and development to the initial launch. The app’s rating improved by 20% and conversion 5X due to the improved UI and reduced steps in the sales pipeline.

I led the project team that designed, integrated, and launched Nest Secure’s first exclusive monitoring service—now part of the Google Home division. I managed UX designers, software engineers, QA analysts, and product marketers to build a new eCommerce site catered to Nest users and brand guidelines with Google branding. Three months from launch, Nest Secure sales represented 28% of total sales. By year-end, Nest Secure sales were over 40% of total sales.

The product vision was to create a CRM tool for an NYC real estate company that specializes in the permitting process for property construction projects. The project was to make initial discoveries to determine the product and market fit, design initial prototypes, and gather requirements that an offshore development team could execute.

LXRInsights is an AI-powered digital marketing platform that elevates Google Ads performance by providing Google Ads AI-generated customer segments, targeting customers with the highest value and, thus, the highest likelihood to repeat shop.

• 56 — Stories Shipped During MVP for Forensic Copilot over 20-week Build
• 5 — Design Partners Recruited for Beta and Pre-sale UAT in Med-legal Domain

Forensic psychiatrists and legal teams had to sift through hundreds of pages per case, making it slow and risky to prepare reports and testimony. GenAI tools hallucinated, lacked traceability, and could not meet medical/legal standards, so experts still relied on manual review.

• Led end-to-end design of a GenAI copilot that turned long clinical and legal documents into a trustworthy assistant embedded in the forensic psychiatry workflow, with a roadmap focused on speed, accuracy, and defensibility.
• Designed RAG pipelines that chunked and embedded records with rich metadata so the copilot could answer questions with precise citations and maintain chain-of-custody expectations.
• Integrated the copilot via APIs into existing document and case systems. Ran weekly feedback loops with clinicians and attorneys to move from demo to daily-use tool.

• Cut manual searching and re-reading time by more than half on key workflows.
• Enabled faster expansion into adjacent legal workflows.
• Shifted clinicians’ perception of GenAI to a dependable assistant embedded in their daily practice.