Overheard
Overheard is an AI-powered customer research platform that conducts live voice interviews with users in the browser and returns decision-grade readouts backed by actual quotes and time-stamped audio clips. Product teams tell the platform what they're deciding, and it designs and runs the study, then synthesizes findings into clear recommendations like "Ship" or "Cut" with supporting evidence. Every finding links to the exact participant, quote, and audio moment for verification.
- Data & Analytics
- Artificial Intelligence
- AI Agents
- Software Only
Funding
Raised to date
$500KRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Founder details are not available yet.
Product
Problem
Product teams make critical decisions—what to build, what to cut, where to focus—without direct, structured evidence from their users. Traditional research is slow, expensive, and often produces vague summaries that don't tie decisions back to what customers actually said.
Solution
Overheard uses an AI voice interviewer to conduct live, in-browser interviews with a company's users, digging into the why behind their behavior. After each study, the platform generates a structured readout that answers the specific question posed, with every finding linked to the supporting participant, quote, and time-stamped audio clip. Teams can test an idea or understand the why behind user behavior, receiving a decision-grade summary that clarifies which option to ship, where to focus, or what is causing drop-off.
Target Audience
Primary users are product managers, founders, and research teams at software companies who need fast, evidence-backed answers from their users to inform roadmap and prioritization decisions.
Features
- AI-powered voice interviewer conducts live interviews in the browser, exploring rationale rather than surface-level answers
- Decision-grade readouts directly answer the company's question, e.g., "Ship Automating invoice data entry" vs. "Cut One-off 'deep research' reports"
- Every finding links to the exact participant, quote, and time-stamped audio clip for verification
- Automated synthesis of responses, showing patterns like "Users already try to automate invoices 4/14" or "Usage breaks when a teammate joins 12/16"
- Flexible study modes: test a specific idea or explore the why behind observed behavior such as post-onboarding drop-off