AI-Powered Research Platform Accelerates Enterprise Customer Insights
Strella, the innovative AI-powered customer research platform, has secured $14 million in Series A funding to expand its revolutionary approach to qualitative research. The funding round, led by Bessemer Venture Partners with participation from Decibel Partners, Bain Future Back Ventures, MVP Ventures and 645 Ventures, comes as enterprises increasingly seek faster, more accurate methods to understand customer behavior and preferences. This significant investment follows the company’s emergence from stealth mode just one year ago, demonstrating rapid market validation for its AI-moderated interview technology.
The startup’s growth trajectory has been remarkable, with revenue increasing tenfold since October, customer base quadrupling to over 40 paying enterprises, and average contract values tripling as the company moves upmarket to serve Fortune 500 clients. This rapid adoption reflects a broader shift toward AI-powered solutions that transform traditional research methodologies across multiple industries.
From Eight Weeks to Days: Revolutionizing Research Timelines
Strella addresses a fundamental challenge that has plagued product teams, marketers, and designers for decades: the painfully slow traditional customer research process. Conventional methods require writing interview guides, recruiting participants, scheduling calls, conducting interviews, taking notes, synthesizing findings, and creating presentations—a workflow that typically consumes eight weeks of highly-skilled labor and often delays critical product decisions.
“Research tends to be bookended by two very strategic steps: first, we have a problem—what research should we do? And second, we’ve done the research—now what are we going to do with it?” explained Lydia Hylton, Strella’s CEO. “All the stuff in the middle tends to be execution and lower-skill work. We view Strella as doing that middle 90% of the work.”
The platform’s AI technology compresses this timeline from weeks to days by conducting voice-based interviews that function like Zoom calls, but with an artificial intelligence agent asking questions, following up on interesting responses, and detecting when participants are being evasive. The system then automatically synthesizes findings, creating highlight reels and charts from unstructured qualitative data.
Unexpected Honesty: Why Participants Trust AI More Than Humans
One of Strella’s most surprising discoveries challenges conventional wisdom about qualitative research: participants appear more honest with AI moderators than with human researchers. This pattern emerged repeatedly during head-to-head comparisons between traditional human-moderated studies and Strella’s AI approach.
“If you’re a designer and you get on a Zoom call with a customer and you say, ‘Do you like my design?’ they’re always gonna say yes. They don’t want to hurt your feelings,” Hylton explained. “But it’s not a problem at all for Strella. They would tell you exactly what they think about it, which is really valuable. It’s very hard to get honest feedback.”
This dynamic has significant business implications, as noted by Brian Santiago, Senior Product Design Manager at Apollo GraphQL: “Before Strella, studies took weeks. Now we get insights in a day—sometimes in just a few hours. And because participants open up more with the AI moderator, the feedback is deeper and more honest.”
Mobile Innovation and Fraud Prevention
A major focus of the Series A funding will be expanding Strella’s recently-launched mobile application, which represents critical competitive differentiation. The mobile app enables persistent screen sharing during interviews—allowing researchers to watch users navigate mobile applications in real time while the AI moderator asks about their experience.
“We are the only player in the market that supports screen sharing on mobile,” Hylton emphasized. “You know, I want to understand what are the pain points with my app? Why do people not seem to be able to find the checkout flow? Well, in order to do that effectively, you’d like to see the user screen while they’re doing an interview.”
The platform also addresses endemic fraud in online surveys, particularly when participants are compensated. Because Strella interviews happen on camera in real time, the AI moderator can detect when someone pauses suspiciously long—perhaps to consult external resources—and flags them as potentially fraudulent. This capability stands in stark contrast to traditional digital platforms where fraud remains a significant challenge.
Technical Differentiation in a Crowded Market
Strella enters a market that includes established players like Qualtrics and numerous AI-powered startups, but the company has developed unique technical capabilities that set it apart. While many competitors began with adaptive surveys—text-based interfaces where users type responses—Strella focused on creating truly conversational AI interviews.
“Our approach is fundamentally better, which is the fact that it is a free form conversation,” Hylton stated. “You never have to control anything. You’re never typing, there’s no buttons, there’s no upload and wait for the next question. It’s completely free form, and that has been an extraordinarily hard product to build.”
The platform’s technical sophistication extends to its ability to improve with use, learning from each customer’s research patterns to fine-tune future interview guides and questions. This continuous improvement cycle creates a powerful competitive advantage, similar to how advanced AI systems evolve through iterative learning processes.
Enterprise Adoption and Future Applications
Strella’s platform now serves major enterprises including Amazon, Duolingo, Apollo GraphQL, and Chobani, collectively conducting thousands of AI-moderated interviews that deliver what the company claims is a 90% average time savings on manual research work. The company is approaching $1 million in revenue after beginning monetization only in January, with month-over-month growth of 50% and zero customer churn to date.
Lindsey Li, Vice President at Bessemer Venture Partners, who led the investment, emphasized the platform’s unique value proposition: “Strella has built highly differentiated technology that enables a continuous interview rather than a survey. We heard time and time again that customers loved this product experience relative to other offerings.”
The technology’s potential extends beyond traditional market research, with applications in product development, user experience testing, and even employee feedback systems. As organizations increasingly recognize the limitations of traditional surveys and the high cost of human-moderated research, AI-powered solutions like Strella offer a compelling alternative.
The Future of Qualitative Research
As Strella continues to evolve, the platform represents a broader shift toward AI-enhanced research methodologies that combine the scalability of quantitative methods with the depth of qualitative insights. The company’s success demonstrates that while regulatory frameworks around AI continue to develop, enterprises are eagerly adopting technologies that deliver tangible business value.
The platform’s ability to maintain high engagement levels—with interviews regularly running 60 to 90 minutes with nearly 100% completion rates—contrasts sharply with traditional survey formats that typically see 60-70% drop-off rates. This engagement, combined with the depth of insights generated, positions Strella as a transformative force in the research industry.
Looking ahead, the company’s vision extends beyond simply automating existing research processes. As Hylton noted, “We think the long game here will be won with a million small product decisions, all of which must be driven by deep empathy for customer pain and an understanding of how best to address their needs.” This philosophy aligns with broader trends in technology development that prioritizes user experience and practical utility over purely technical features.
With its recent funding and growing enterprise adoption, Strella appears well-positioned to continue reshaping how organizations understand their customers, potentially establishing what Li described as “the system of truth for all qualitative insights” within forward-thinking enterprises.
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