One year after emerging from stealth, Strella has raised $14 million in Series A funding to expand its AI-powered customer research platform, the company announced Thursday. The round, led by Bessemer Venture Partners with participation from Decibel Partners, Bain Future Back Ventures, MVP Ventures and 645 Ventures, comes as enterprises increasingly turn to artificial intelligence to understand customers faster and more deeply than traditional methods allow.
The investment marks a sharp acceleration for the startup founded by Lydia Hylton and Priya Krishnan, two former consultants and product managers who watched companies struggle with a customer research process that could take eight weeks from start to finish. Since October, Strella has grown revenue tenfold, quadrupled its customer base to more than 40 paying enterprises, and tripled its average contract values by moving upmarket to serve Fortune 500 companies.
"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?" said Hylton, Strella's CEO, in an exclusive interview with VentureBeat. "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 now serves 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.
How AI-powered interviews compress eight-week research projects into days
Strella's technology addresses a workflow that has frustrated product teams, marketers, and designers for decades. Traditional customer research requires writing interview guides, recruiting participants, scheduling calls, conducting interviews, taking notes, synthesizing findings, and creating presentations — a process that consumes weeks of highly-skilled labor and often delays critical product decisions.
The platform compresses that timeline to days by using AI to moderate voice-based interviews that run like Zoom calls, but with an artificial intelligence agent asking questions, following up on interesting responses, and detecting when participants are being evasive or fraudulent. The system then synthesizes findings automatically, creating highlight reels and charts from unstructured qualitative data.
"It used to take eight weeks. Now you can do it in the span of a couple days," Hylton told VentureBeat. "The primary technology is through an AI-moderated interview. It's like being in a Zoom call with an AI instead of a human — it's completely free form and voice based."
Critically, the platform also supports human moderators joining the same calls, reflecting the founders' belief that humans won't disappear from the research process. "Human moderation won't go away, which is why we've supported human moderation from our Genesis," Hylton said. "Research tends to be bookended by two very strategic steps: we have a problem, what's the research that we should do? And we've done the research, now what are we going to do with it? 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."
Why customers tell AI moderators the truth they won't share with humans
One of Strella's most surprising findings challenges assumptions about AI in qualitative research: participants appear more honest with AI moderators than with humans. The founders discovered this pattern repeatedly as customers ran 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."
Krishnan, Strella's COO, said companies initially worried about using AI and "eroding quality," but the platform has "actually found the opposite to be true. People are much more open and honest with an AI moderator, and so the level of insight that you get is much richer because people are giving their unfiltered feedback."
This dynamic has practical business implications. Brian Santiago, Senior Product Design Manager at Apollo GraphQL, said in a statement: "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."
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 ChatGPT — and flags them as potentially fraudulent. "We are fraud resistant," Hylton said, contrasting this with traditional surveys where fraud rates can be substantial.
Solving mobile app research with persistent screen sharing technology
A major focus of the Series A funding will be expanding Strella's recently-launched mobile application, which Krishnan identified as 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 said. "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."
For consumer-facing companies where mobile represents the primary customer interface, this capability opens entirely new use cases. The founders noted that "several of our customers didn't do research before" but have now built research practices around Strella because the platform finally made mobile research accessible at scale.
The platform also supports embedding traditional survey question types directly into the conversational interview, approaching what Hylton called "feature parity with a survey" while maintaining the engagement advantages of a natural conversation. Strella interviews regularly run 60 to 90 minutes with nearly 100% completion rates—a duration that would see 60-70% drop-off in a traditional survey format.
How Strella differentiated in a market crowded with AI research startups
Strella enters a market that appears crowded at first glance, with established players like Qualtrics and a wave of AI-powered startups promising to transform customer research. The founders themselves initially pursued a different approach — synthetic respondents, or "digital twins" that simulate customer perspectives using large language models.
"We actually pivoted from that. That was our initial idea," Hylton revealed, referring to synthetic respondents. "People are very intrigued by that concept, but found in practice, no willingness to pay right now."
Recent research suggesting companies could use language models as digital twins for customer feedback has reignited interest in that approach. But Hylton remains skeptical: "The capabilities of the LLMs as they are today are not good enough, in my opinion, to justify a standalone company. Right now you could just ask ChatGPT, 'What would new users of Duolingo think about this ad copy?' You can do that. Adding the standalone idea of a synthetic panel is sort of just putting a wrapper on that."
Instead, Strella's bet is that the real value lies in collecting proprietary qualitative data at scale — building what could become "the system of truth for all qualitative insights" within enterprises, as Lindsey Li, Vice President at Bessemer Venture Partners, described it.
Li, who led the investment just one year after Strella emerged from stealth, said the firm was convinced by both the technology and the team. "Strella has built highly differentiated technology that enables a continuous interview rather than a survey," Li said. "We heard time and time again that customers loved this product experience relative to other offerings."
On the defensibility question that concerns many AI investors, Li emphasized product execution over patents: "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. Lydia and Priya exhibit that in spades."
The founders point to technical depth that's difficult to replicate. Most competitors started with adaptive surveys — text-based interfaces where users type responses and wait for the next question. Some have added voice, but typically as uploaded audio clips rather than free-flowing conversation.
"Our approach is fundamentally better, which is the fact that it is a free form conversation," Hylton said. "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. There's a tremendous amount of IP in the way that we prompt our moderator, the way that we run analysis."
The platform also improves with use, learning from each customer's research patterns to fine-tune future interview guides and questions. "Our product gets better for our customers as they continue to use us," Hylton said. All research accumulates in a central repository where teams can generate new insights by chatting with the data or creating visualizations from previously unstructured qualitative feedback.
Creating new research budgets instead of just automating existing ones
Perhaps more important than displacing existing research is expanding the total market. Krishnan said growth has been "fundamentally related to our product" creating new research that wouldn't have happened otherwise.
"We have expanded the use cases in which people would conduct research," Krishnan explained. "Several of our customers didn't do research before, have always wanted to do research, but didn't have a dedicated researcher or team at their company that was devoted to it, and have purchased Strella to kick off and enable their research practice. That's been really cool where we've seen this market just opening up."
This expansion comes as enterprises face mounting pressure to improve customer experience amid declining satisfaction scores. According to Forrester Research's 2024 Customer Experience Index, customer experience quality has declined for three consecutive years — an unprecedented trend. The report found that 39% of brands saw CX quality deteriorate, with declines across effectiveness, ease, and emotional connection.
Meanwhile, Deloitte's 2025 Technology, Media & Telecommunications Predictions report forecasts that 25% of enterprises using generative AI will deploy AI agents by 2025, growing to 50% by 2027. The report specifically highlighted AI's potential to enhance customer satisfaction by 15-20% while reducing cost to serve by 20-30% when properly implemented.
Gartner identified conversational user interfaces — the category Strella inhabits — as one of three technologies poised to transform customer service by 2028, noting that "customers increasingly expect to be able to interact with the applications they use in a natural way."
Against this backdrop, Li sees substantial room for growth. "UX Research is a sub-sector of the $140B+ global market-research industry," Li said. "This includes both the software layer historically (~$430M) and professional services spend on UX research, design, product strategy, etc. which is conservatively estimated to be ~$6.4B+ annually. As software in this vertical, led by Strella, becomes more powerful, we believe the TAM will continue to expand meaningfully."
Making customer feedback accessible across the enterprise, not just research teams
The founders describe their mission as "democratizing access to the customer" — making it possible for anyone in an organization to understand customer perspectives without waiting for dedicated research teams to complete months-long studies.
"Many, many, many positions in the organization would like to get customer feedback, but it's so hard right now," Hylton said. With Strella, she explained, someone can "log into Strella and through a chat, create any highlight reel that you want and actually see customers in their own words answering the question that you have based on the research that's already been done."
This video-first approach to research repositories changes organizational dynamics around customer feedback. "Then you can say, 'Okay, engineering team, we need to build this feature. And here's the customer actually saying it,'" Hylton continued. "'This is not me. This isn't politics. Here are seven customers saying they can't find the Checkout button.' The fact that we are a very video-based platform really allows us to do that quickly and painlessly."
The company has moved decisively upmarket, with contract values now typically in the five-figure range and "several six figure contracts" signed, according to Krishnan. The pricing strategy reflects a premium positioning: "Our product is very good, it's very premium. We're charging based on the value it provides to customers," Krishnan said, rather than competing on cost alone.
This approach appears to be working. The company reports 100% conversion from pilot programs to paid contracts and zero churn among its 40-45 customers, with month-over-month revenue growth of 50%.
The roadmap: Computer vision, agentic AI, and human-machine collaboration
The Series A funding will primarily support scaling product and go-to-market teams. "We're really confident that we have product-market fit," Hylton said. "And now the question is execution, and we want to hire a lot of really talented people to help us execute."
On the product roadmap, Hylton emphasized continued focus on the participant experience as the key to winning the market. "Everything else is downstream of a joyful participant experience," she said, including "the quality of insights, the amount you have to pay people to do the interviews, and the way that your customers feel about a company."
Near-term priorities include adding visual capabilities so the AI moderator can respond to facial expressions and other nonverbal cues, and building more sophisticated collaboration features between human researchers and AI moderators. "Maybe you want to listen while an AI moderator is running a call and you might want to be able to jump in with specific questions," Hylton said. "Or you want to run an interview yourself, but you want the moderator to be there as backup or to help you."
These features move toward what the industry calls "agentic AI" — systems that can act more autonomously while still collaborating with humans. The founders see this human-AI collaboration, rather than full automation, as the sustainable path forward.
"We believe that a lot of the really strategic work that companies do will continue to be human moderated," Hylton said. "And you can still do that through Strella and just use us for synthesis in those cases."
For Li and Bessemer, the bet is on founders who understand this nuance. "Lydia and Priya exhibit the exact archetype of founders we are excited to partner with for the long term — customer-obsessed, transparent, thoughtful, and singularly driven towards the home-run scenario," she said.
The company declined to disclose specific revenue figures or valuation. With the new funding, Strella has now raised $18 million total, including a $4 million seed round led by Decibel Partners announced in October.
As Strella scales, the founders remain focused on a vision where technology enhances rather than eliminates human judgment—where an engineering team doesn't just read a research report, but watches seven customers struggle to find the same button. Where a product manager can query months of accumulated interviews in seconds. Where companies don't choose between speed and depth, but get both.
"The interesting part of the business is actually collecting that proprietary dataset, collecting qualitative research at scale," Hylton said, describing what she sees as Strella's long-term moat. Not replacing the researcher, but making everyone in the company one.