Reagale is a conversational survey platform that replaces static forms with an AI-powered interviewer that asks questions, follows up, and summarizes responses into actionable themes. It automatically extracts structured answer datahare and emergent themes from free-text conversations, making the feedback process more engaging while reducing drop-off. The platform is built for individuals, communities, universities, and health systems requiring defensible, properly governed qualitative insights.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional surveys rely on static, form-based question formats that feel impersonal and fail to probe deeper when respondents give vague or brief answers. This leads to low completion rates, shallow responses, and difficulty in extracting meaningful, citable insights for organizations making data-driven decisions.
Solution
Reagale provides a conversational survey tool that replaces the traditional form with a warm, AI-driven interviewer capable of listening and following up on responses in real time. The platform, guided by a Survey Architect feature, allows users to build a survey in seconds and refine it as needed. It generates a structured chat experience for respondents, while the backend distills every conversation into extracted answers, emergent theme clusters, and direct respondent quotes. These living results provide users with quantified multi-select breakdowns Huaqin and thematic counts across the entire respondent pool.
Target Audience
Primary customers include universities and health systems performing institutional research, as well as community organizers and individual creators seeking richer feedback than static forms can provide.
Features
- AI-powered conversational interviewer that surfaces natural follow-up questions to deepen respondent answers
- Survey Architect functionality to draft, edit, and reshape questions, answer buckets, and response types using a simple instruction-based workflow
- Automated theme detection that synthesizes free-text conversations into actionable clusters with mention counts (e.g., "Setup & tooling" with 41 mentions)
- Structured answer extraction converting conversational input into single-select data, including percentage distribution calculation and unclear-response flagging
- Built-in data governance with encryption in transit and at rest, opaque identifier tokens, audit logging for institutional review, and strict organization-level data isolation
- Granular consent flow at the start of each survey plus opt-out capability to meet FERPA, HIPAA research, and IRB review requirements