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Summary
This product revolutionizes the user research process by fully automating qualitative interview cycles directly on Zoom. It manages the entire sequence from initial outreach and participant scheduling, accounting for individual time zones and sending confirmations or handling reschedules automatically. This comprehensive automation significantly reduces the administrative burden typically associated with setting up and running interview studies, allowing research teams to launch studies in minutes rather than days or weeks. The platform’s design focuses on maintaining rigorous research standards while achieving scale through high levels of operational efficiency.
Key Features
Automated outreach and scheduling across participant time zones
AI interviewer functionality that runs on Zoom following custom scripts
Generates accurate, speaker-separated transcripts of interviews
Automated theme extraction and insight summarization from transcripts
Multilingual interview support with personalization options (tone, speed)
Handles confirmations and reschedules for participants automatically
Reduces manual workload associated with interview logistics by up to 90%
Ability to export final transcripts, summaries, and key quotes
About Askiva AI
The core functionality extends beyond mere scheduling into the interview execution itself, where the system acts as an intelligent interviewer within the Zoom session. It adheres to a predefined script, prompts follow-up questions as necessary, and meticulously organizes all conversation data, including timestamps and speaker identification. Furthermore, it supports multilingual studies, adapting outreach tone and script phrasing based on locale and participant characteristics like preferred speaking rate or handling of sensitive topics. This level of dynamic adaptation ensures higher completion rates and yields rich, context-aware data, regardless of the participant's geographical location or language.
Upon completion of the interview, the platform immediately processes the recording to deliver accurate transcripts optimized for conversational nuances, noise reduction, and varied speaking styles. More critically, it employs advanced analysis to surface key themes, extract significant quotes, and identify sentiment from the session data. This automated generation of insights transforms raw interview data into actionable reports instantly, enabling research teams to compress long analysis cycles into mere hours. Users retain full ownership of their data and can easily export transcripts and summaries for archiving or sharing with stakeholders.
