
Preventing Manual Errors That Cost Millions
Led AI/ML design for $9-figure tech business—$1.1M+ ARR, 30% efficiency gain, $XXXK–$XM+ cost reduced from manual errors per incident.
*De-identified for the NDA.
Industry
B2B
SaaS
Enterprise UX
AI/ML
Role
Senior Product Designer
Team
2 Product Designers • 2 UX Researchers • 1 PM • 5 Developers • 3 Data Scientists
Skills
B2B SaaS Solutions • Prototyping • Scalable Design Systems • Stakeholder Interviews • User Flows • Usability Testing • Data Analysis • Accessibility (WCAG)
Impacts
01 · The Context
My role and leadership context.
Led UX design and management in fast-paced, high-stress environment.
Partnered with agile cross-functional teams under tight deadlines: Product, Design, Research, Engineering and Data Teams.
Owned end-to-end UX strategy, research, design, and delivery.
Made strategic trade-off decisions under uncertainty to maximize impact.
Technical achievement.
Successfully delivered B2B SaaS product leveraging AI/ML, data infrastructure, and comprehensive logging with the client’s security system.
AI-powered error prevention for high-stakes production environments.
Enterprise UX solutions for issue tracking, system updates, and data analysis/visualization.
Real-time production monitoring with AI/ML predictive analytics from big data.
Business goal
Solutions support expansion on production sites and product lines.
Solutions help staff fast address production issues to mitigate risk and cost.
Solutions integrated with data and infrastructure to apply AI/ML patterns for long-term production stability and reliability.
Impacts






