Askiva AI

What is Askiva AI?

Askiva AI automates the entire qualitative research interview workflow from start to finish. A researcher sets a study topic, uploads a participant list (XLSX), defines target number of completes and session duration, then lets Askiva handle everything else: sending personalized email invites, detecting each participant's local time zone and booking availability, creating unique Zoom meeting links, joining calls autonomously to conduct the interview following a structured script, generating accurate transcripts, and delivering grouped themes with cited quotes in a dashboard. The AI interviewer supports 10+ languages, adapts its tone and speaking rate to each participant, and handles follow-up questions dynamically. The entire cycle from study setup to insights typically takes minutes for setup and hours for delivery instead of weeks.

How to use Askiva AI?

1. Create a study by entering your research topic and setting the language — Askiva can generate a question script with AI in under minutes.
2. Upload your participant list as an XLSX file with names and emails.
3. Set your target number of completed interviews, study duration, and optional settings like availability windows and calendar integration.
4. Preview the AI-generated invite email and interview script, then optionally run a test interview to validate the flow.
5. Launch the study — Askiva contacts participants, books slots, joins Zoom, conducts interviews, transcribes them, and delivers themes, quotes, and summaries in your dashboard.

Core Features

• Automated Interview Scheduling — Sends personalized email invites, proposes time slots based on each participant's local time zone, and handles confirmations, reschedules, and cancellations without manual follow-up.
• AI Zoom Interviewer — Joins each meeting link autonomously, follows the structured interview script, asks context-aware follow-up questions, and manages silence and pacing across different speaking styles.
• Multilingual Support with Persona Adaptation — Runs studies in + languages, detecting each participant's locale and adjusting tone, speaking rate, and phrasing to maximize completion rates globally.
• High-Accuracy Transcription — Produces interview transcripts optimized for conversational speech with speaker separation, noise reduction, and accent handling — accurate enough for research-grade decisions.
• Automated Theme Analysis — Groups responses into themes, surfaces key quotes, and provides sentiment analysis across all completed interviews in a shareable dashboard.
• Privacy-First Data Ownership — Researchers own their data; transcripts and summaries are stored in the user's account and can be downloaded or deleted at any time, with no data used for model training.
• Export & Sharing — Export transcripts, summaries, and key quotes as PDFs directly from the dashboard for stakeholder reporting and archival.

Use Cases

• Product Discovery Research — Product teams run discovery interviews with – users in days instead of weeks, getting structured themes and quotes ready for sprint planning.
• UX Testing & Usability Studies — UX researchers automate participant recruitment follow-up and session logistics, focusing their time on analyzing insights rather than scheduling.
• Academic Research — University research teams conduct multilingual qualitative studies across global participants without needing research assistants to manage logistics.
• Customer Success & Churn Analysis — Companies run automated exit interviews or NPS deep-dives at scale, surfacing patterns across many customers without taxing the CS team.
• Market Research for Global Launches — Agencies and startups run multilingual market validation studies across multiple regions simultaneously, with locale-appropriate interviewer tone per participant.