When co-founders Florian Juengermann and Alfred Wahlforss struggled to understand their own customers, they didn’t just fix the problem—they turned it into a business model. After launching BeFake, a viral image-generation app that gained 20,000 downloads in a single day in 2023, the duo faced a familiar startup dilemma: people loved their product, but they didn’t stick around.

“We were basically desperate to understand how to get customers to stick,” said Wahlforss. But instead of hiring costly consultants or running delayed focus groups, they thought—what if an AI could simply ask every user what they felt?

That spark led to Listen Labs, a company designed to bring speed, scale, and intelligence to market research using the latest in large language models (LLMs). Their prototype was so effective at capturing and synthesizing feedback that they quickly sold BeFake and committed full-time to Listen Labs.

Sequoia’s $40 Billion Bet on AI-Driven Feedback

Backing this bold vision is Sequoia Capital's Bryan Schreier, the first investor in customer experience platform Qualtrics. Schreier had been hunting for a company that could upend the traditional market research model—dominated for decades by expensive consultants and glacially slow focus groups. Listen Labs was exactly what he was waiting for.

“Most companies talk about being customer-obsessed, but they lack the tools to really be that,” Schreier said. “You can run analytics or do a focus group once a year—but that’s slow, expensive, and outdated. Listen Labs is the AI-first approach this space has been begging for.”

So far, it seems the gamble is paying off. Big-name clients like Microsoft, Canva, and Chubbies already use the platform to generate questions, identify participants, and conduct real-time interviews across languages and geographies—all within hours, not weeks. Then, LLMs convert that raw feedback into summary reports, highlight reels, and even PowerPoint presentations.

Listening in Every Language, Powered by AI

One of Listen’s core strengths is its adaptability. “We don’t rely on a single LLM,” says Juengermann. “We use a mix of models, so we can stay agile as new capabilities emerge.” These models are fine-tuned not only to ask context-aware questions but also to operate in multiple languages—crucial for clients with global reach.

During a research project with Canva, for instance, Listen Labs’ AI held interviews in dozens of languages, then instantly translated insights into English. That level of reach and coherence, Juengermann points out, wouldn’t have been possible with early versions of ChatGPT. “Back then, it couldn’t even follow basic instructions,” he says. “It wasn’t until GPT-4 that things changed—now the AI can understand business context, nuance, and tone.”

Dogfooding Their Way to Product-Market Fit

Naturally, the startup uses its own tech religiously. From A/B testing their ads to tweaking landing pages, Juengermann and Wahlforss are constantly feeding user input back into the product. Ironically, one of their biggest insights came from AI research on their own target audience.

“We assumed product managers would be our main users,” says Wahlforss. “But Listen told us otherwise—it interviewed 50 PMs and 50 marketers and clearly showed that marketing folks were the real power users.”

Next Up—An AI That Doesn’t Just Listen, But Acts

Now, the founders are looking ahead. The next evolution? A proactive AI agent that doesn’t just analyze feedback—it anticipates what customers want and acts on it. With OpenAI’s latest models now surpassing even Wahlforss’ own interviewing skills, they’re building a system that thinks ahead.

In a world where user insights have become the new gold, Listen Labs is proving that sometimes, all you have to do is ask—and really listen.