From research to results, Mr. Ravi Palwe shows how trusted AI and strong design systems make complex work feel simple and measurably better.

He is a senior UX leader and product designer with two decades of turning complex systems into simple, high-performing experiences. HFI-Certified and relentlessly evidence-based, he leads with research, sharp strategy, and clean execution.

His work pairs customer insight with disciplined delivery. He led a full web-experience reimagining that raised CSAT 45% and cut complaints 60%. He overhauled a high-stakes financial workflow to reduce task time 40% and drove a double-digit lift in mobile activation. His AI initiatives focus on what actually moves the needle: smarter on boarding, semantic search, tailored recommendations, and faster research synthesis that helps teams decide and ship sooner.

Most recently, he helped build an AI-driven wealth-management advisor for one of North America’s largest wealth-management companies pairing transparent recommendations with compliance-minded design so customers get guidance they can trust. He’s known for scaling design systems with clear standards and governance, making accessibility (WCAG) a non-negotiable, and cultivating a healthy critique culture that raises quality without slowing teams down.

His toolkit spans the full stack of UX. He plans research with clear learning goals, mixes methods like interviews, diary studies, card sorts, tree tests, and RITE usability cycles, then connects the dots with JTBD, journey maps, and service blueprints. He translates findings into crisp information architecture, task flows, and high-fidelity prototypes. He pairs this with strong content design, error-state planning, and localization awareness so screens read like they were written for real people, not committees.

He works end-to-end-from discovery to handoff and QA partnering tightly with Product, Engineering, Data, Legal, and Compliance. He brings the same rigor to measurement, using experimentation and product analytics (A/B tests, funnels, CSAT, CES, NPS, OKRs) to prove what works and cut what doesn’t. The through-line is simple: ship experiences that are understandable, trustworthy, and measurably better than last quarter.