Candor is a synthetic user research platform that enables qualitative research using AI-powered participants grounded in real evidence. It allows users to interview synthetic personas about problems, concepts, and pricing, with every answer traceable to its source evidence. This platform helps teams sharpen their research questions and validate ideas before investing in costly human recruiting.
The core functionality revolves around creating highly realistic synthetic participants. Users describe their target audience, and Candor either searches for published data (government statistics, industry reports, peer-reviewed research) or integrates uploaded documents (customer interviews, survey data, market reports). This evidence-based approach ensures that participant attributes are not based on AI imagination but on verifiable sources, with each profile field labeled with its evidence provenance.
Candor simplifies the research process by recommending study types and building interview guides based on user objectives. It supports various use cases, including:
- Problem discovery: Uncovering real pains and unmet needs.
- Problem validation: Pressure-testing specific problems to determine their worth.
- Concept testing: Evaluating products, features, names, or value propositions.
- Price testing: Determining optimal pricing strategies and identifying willingness-to-pay thresholds.
The platform's interviewing methodology is designed with research rigor, adapting to each participant uniquely. Unlike other tools that follow a rigid script, Candor's interviewer can follow interesting conversational threads, delve deeper into unexpected insights, and move on when a topic is sufficiently explored. This dynamic approach helps surface valuable findings that might not have been part of the initial interview guide.
After interviews, Candor synthesizes the findings into clear, actionable reports, highlighting strong themes, areas of disagreement, and key takeaways. Full interview transcripts are provided, allowing users to verify any finding against the original conversation.
Unique differentiators of Candor include:
- Differentiated modeling: Business buyers and consumers are modeled with distinct personality profiles, decision frameworks, and buying triggers.
- Participant memory: Synthetic participants remember past conversations, allowing for longitudinal studies or follow-up interviews with consistent personas.
- Push-back capability: Participants are designed to hold positions, disagree, and stay in character, avoiding generic AI agreeableness.
- Critic review: A separate AI critic reviews every participant response against their prior statements and underlying evidence to catch contradictions.
Candor is ideal for product teams and PMs needing faster insights, startups and consultants requiring quick validation, research and insights leaders looking to optimize panel budgets, and innovation teams needing evidence-based decisions on tight deadlines. It provides decision-grade signals in hours, empowering teams to bring evidence to their next decision.
