Outset is an AI-moderated user research platform that enables product, UX, and research teams to conduct live, one-on-one qualitative interviews at scale. The platform is designed to help organizations collect in-depth customer insights more efficiently than traditional moderated interviews or survey-based research methods. Outset uses an AI interviewer to facilitate real-time, conversational interviews with research participants. During each session, the AI asks adaptive follow-up questions based on participant responses, allowing teams to explore motivations, context, and emotional drivers without relying on static scripts. This approach supports qualitative research use cases that typically require human moderation, while reducing scheduling constraints and operational overhead. The platform is commonly used by UX researchers, product managers, design teams, and insights teams at mid-sized and enterprise organizations. Typical use cases include product discovery, usability testing, concept evaluation, customer feedback collection, and exploratory research conducted across distributed or global participant groups. Outset supports end-to-end research workflows, from interview execution to insight synthesis. After each interview, teams receive automatically generated transcripts, summaries, and themes, making it easier to analyze findings and share results with stakeholders across product, design, and leadership teams. Key features and capabilities include: -AI-moderated, live qualitative interviews with dynamic, context-aware follow-up questions -Support for one-on-one interviews conducted asynchronously across time zones -Automated transcription and structured interview summaries -Centralized access to qualitative insights for collaboration and reporting Primary benefits for organizations include: -Increased research velocity without increasing headcount -Greater consistency across interviews compared to manual moderation -Improved accessibility to qualitative insights for cross-functional teams Outset is typically implemented by teams seeking to scale qualitative research while maintaining methodological rigor, security standards, and alignment with existing research and design workflows.