Koji is an AI customer research platform for conducting conversational interviews with users and turning their responses into research findings. It is designed to replace some of the scheduling and manual work involved in interviews or surveys: Koji generates questions, asks adaptive follow-ups, collects participant responses, and summarizes themes, quotes, and recommendations. The stated goal is to help teams move from research questions to actionable insights in hours rather than weeks.
Key features
Koji’s central feature is its automated conversational interview process. Rather than relying only on fixed survey questions, it can follow up adaptively during conversations. This approach is intended to gather deeper qualitative feedback while allowing teams to hear from multiple users without arranging individual calls.
The platform also supports several steps around the interview itself. It can generate interview scripts, collect participant responses, and produce research reports. After responses are collected, its listed analysis tools include automated insight summaries, theme and pattern detection, and quote extraction. Persona discovery assistance and continuous feedback collection are also included among its stated features.
Together, these capabilities make Koji more than a question-generation tool: it is presented as a workflow for setting up interviews, collecting feedback, and organizing the findings. The product page describes its output as including patterns, quotes, and recommendations, though it does not explain the analysis process or how users review and edit those outputs.
Where teams can use it
Koji is positioned for founders, product managers, researchers, go-to-market teams, marketers, and customer success teams. Founders can use conversational feedback to test demand and refine ideas before building. Product teams can gather structured responses after releases and look for recurring feedback that may inform improvements.
For marketing and growth work, Koji can help teams learn how customers describe their problems and use that language to refine messaging and positioning. Customer success teams can interview churned or unhappy users to investigate retention issues and onboarding experiences. UX researchers may find the automated interview and analysis workflow useful for gathering qualitative input at scale, particularly when manual transcription and analysis are burdensome.
These examples describe research and feedback activities rather than a narrow industry-specific use. Koji may be most relevant when a team needs qualitative customer insight but does not have the time or staffing to conduct many interviews manually.
What to consider
Koji’s description emphasizes automated interviews and AI-generated analysis, but the available product information does not specify how participant recruitment or interview distribution works. It also does not explain supported languages, integrations, data-handling practices, or how researchers can inspect and validate AI-generated findings. Teams should clarify these details against their own research requirements before relying on the platform for a particular workflow.
The page also does not provide information about interview limits or the amount of setup and review required. Automation can reduce manual effort, but it does not establish that every research question can be answered without human judgment. The quality and usefulness of findings will still depend on the questions asked and how the team interprets the responses.
Verdict
Koji combines automated, adaptive user interviews with tools for synthesizing qualitative feedback. Its strongest fit is for teams that need to validate ideas, understand customers, evaluate product feedback, or improve messaging without arranging a large number of manual calls. The feature set covers interview generation, response collection, and analysis, giving it a broad role in the research process. However, information about practical setup, integrations, privacy, and review controls is not provided, so those areas remain important points to investigate.
