Social Physics Research develops AI-guided conversational research platforms that replace static surveys with adaptive, structured interviews. Its flagship product, InsightFlow, uses an AI moderator to probe responses and convert qualitative data into quantitative analytics for political campaigns and policy organizations. The platform delivers thematic coding, sentiment scoring, and linguistic clustering to uncover voter reasoning at scale.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional polling and static surveys capture fixed responses but provide limited insight into the reasoning, language, and emotional framing behind voter opinions. Researchers struggle to identify emerging signals and unanticipated perspectives because structured questions constrain responses and follow-up probing requires costly manual effort.
Solution
InsightFlow is an AI-guided qualitative research platform that replaces static surveys with structured conversational interviews conducted by an AI moderator. Each interview follows a researcher-defined branching flow with scripted entry, probe triggers, and controlled exit, ensuring reproducible and defensible research. The AI moderator probes for reasoning, follows up on ambiguity, and adapts within the defined architecture, delivering qualitative depth at quantitative scale. Insights are converted into actionable analytics including thematic coding, sentiment scoring with intensity weighting, and linguistic clustering across respondents. The platform is developed by Social Physics Research and designed to strengthen interpretation of quantitative findings rather than replace polling.
Target Audience
Primary customers are political campaigns, policy institutes, and advocacy organizations conducting voter research or message testing.
Features
- AI moderator conducts concurrent structured interviews with real-time follow-up probing on every response
- Researcher-defined conversation architecture with branching logic, probe triggers, and controlled exit protocols
- Automated thematic coding with segment-level breakdowns and linguistic clustering across respondents
- Sentiment scoring with intensity weighting and response quality/engagement metrics
- Bias monitoring on moderator behavior plus full data export, consent tracking, and deletion API
- Applied to campaign message testing, policy reaction analysis, and turnout motivation research