Manual documentation consumes valuable time and attention. I identified an opportunity to reduce this burden with ambient intelligence, enabling AI to quietly draft structured notes in real time. Through quick, iterative prototypes, we designed a context-aware assistant that helps reclaim time, maintain accuracy, and stay focused.

Critical decisions often depend on inaccessible or buried insights. I applied conversational AI to make analytics more accessible, enabling natural language queries to surface targeted, evidence-based recommendations within workflows — improving confidence, speeding decisions, and maintaining focus.

Decisions about high-stakes, complex information are often made under pressure. I built an AI-driven workflow to quickly parse and summarize intricate details, enabling informed decisions faster, with fewer errors and greater confidence.

Coordinating across teams and disciplines is inherently complex. We used AI to bring clarity and structure to collaborative workflows, suggesting task lists, plans, and summaries to guide alignment — empowering teams to adapt quickly and deliver better outcomes together.

Organizational knowledge is often scattered and hard to access. I unlocked this knowledge with an AI assistant, giving teams fast, intuitive access to policies, best practices, and key documents through natural language queries — reducing wasted time and enabling higher-value work.

Proactive planning at scale is critical yet often reactive and fragmented. We applied predictive analytics to anticipate risks, analyze trends and signals, and surface actionable foresight — enabling earlier interventions, smarter planning, and more effective resource use.

Back-office processes are time-consuming and error-prone. I’m leveraging AI responsibly to streamline these workflows, from automated verifications and denial pattern analysis to coding assistance — saving costs, improving speed, and reducing staff burden while maintaining trust.