Listen Labs Raises $69 Million To Scale AI Customer Interviews

Listen Labs Turns AI Interviews Into A Funding Case

Listen Labs has raised $69 million in Series B funding for an AI customer-research platform that tries to make interviews as fast as software teams now expect their product cycles to be.

Ribbit Capital led the round, with Evantic, Sequoia Capital, Conviction and Pear VC also involved.

The financing values Listen Labs at $500 million and brings total capital raised to $100 million.

The company says it has grown annualized revenue by 15x to eight figures in nine months since launch, while running over one million AI-powered interviews.

The Product Replaces A Survey-Or-Interview Trade-Off

Listen Labs is built around an AI researcher that helps create a study, recruits participants, conducts open-ended interviews and turns the results into reports, highlight reels and slide decks.

The company says it draws participants from a global network of 30 million people.

Alfred Wahlforss, the startup's founder and chief executive, argues that surveys can produce shallow precision while human interviews do not scale.

His narrower claim is that video interviews with AI follow-up questions can preserve more of the detail from qualitative research while shortening the time between a product question and a customer answer.

Customer Proof Is The Stronger Signal

Named customer deployments make the funding round more than a standard AI startup capital story.

For Microsoft's 50th anniversary work, Listen Labs gathered global customer video stories within a day; the comparable manual process would normally take six to eight weeks.

Simple Modern used the platform to test a product concept by spending about an hour writing questions, an hour launching a study and 2.5 hours gathering feedback from 120 people.

Chubbies said youth research participation rose 24x, from 5 to 120 participants, after the brand used Listen to avoid scheduling problems around traditional focus groups.

Emeritus reported a different operational result.

The online education company said approximately 20% of earlier survey responses had been fraudulent or low quality, while Listen reduced that problem to almost zero.

Listen says its quality guard checks LinkedIn profiles against video responses, reviews consistency across answers and flags suspicious patterns.

The Next Risk Is Automated Decision-Making

The company is moving beyond interviews toward simulated customer voices and agentic workflows that could act on research findings.

Wahlforss said Listen wants companies to keep humans in the loop, and he said the platform does not train on customer data while automatically scrubbing sensitive PII.

That roadmap is useful but also raises the main checkpoint for enterprise buyers.

Listen Labs can point to Microsoft, Simple Modern, Chubbies and Emeritus as early proof that AI interviews can shorten research cycles.

Its next test is whether companies trust the same system when it starts moving from customer insight into simulated users and automated follow-up actions.