One yr after emerging from stealth, Strella has raised $14 million in Series A funding to expand its AI-powered customer research platform, the corporate 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 grasp customers faster and more deeply than traditional methods allow.
The investment marks a pointy acceleration for the startup founded by Lydia Hylton and Priya Krishnan, two former consultants and product managers who watched firms struggle with a customer research process that might take eight weeks from start to complete. Since October, Strella has grown revenue tenfold, quadrupled its customer base to greater than 40 paying enterprises, and tripled its average contract values by moving upmarket to serve Fortune 500 firms.
“Research tends to be bookended by two very strategic steps: first, we now have an issue—what research should we do? And second, we have 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 center 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 hundreds of AI-moderated interviews that deliver what the corporate claims is a 90% average time savings on manual research work. The company is approaching $1 million in revenue after starting monetization only in January, with month-over-month growth of fifty% and 0 customer churn thus far.
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 a long time. 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 infrequently delays critical product decisions.
The platform compresses that timeline to days through the use of AI to moderate voice-based interviews that run like Zoom calls, but with a synthetic intelligence agent asking questions, following up on interesting responses, and detecting when participants are being evasive or fraudulent. The system then synthesizes findings routinely, creating highlight reels and charts from unstructured qualitative data.
“It used to take eight weeks. Now you possibly can do it within the span of a pair days,” Hylton told VentureBeat. “The primary technology is thru an AI-moderated interview. It’s like being in a Zoom call with an AI as an alternative of a human — it’s completely free form and voice based.”
Critically, the platform also supports human moderators joining the identical calls, reflecting the founders’ belief that humans won’t disappear from the research process. “Human moderation won’t go away, which is why we have supported human moderation from our Genesis,” Hylton said. “Research tends to be bookended by two very strategic steps: we now have an issue, what is the research that we must always do? And we have done the research, now what are we going to do with it? All the stuff in the center 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 reality they will not 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 are a designer and also you get on a Zoom call with a customer and also you say, ‘Do you want my design?’ they’re all the time gonna say yes. They don’t need to harm your feelings,” Hylton explained. “But it is not an issue in any respect for Strella. They would let you know exactly what they consider it, which is absolutely helpful. It’s very hard to get honest feedback.”
Krishnan, Strella’s COO, said firms initially nervous about using AI and “eroding quality,” however the platform has “actually found the alternative to be true. People are rather more open and honest with an AI moderator, and so the extent of insight that you just get is way richer because individuals are giving their unfiltered feedback.”
This dynamic has practical business implications. Brian Santiago, Senior Product Design Manager at Apollo GraphQL, said in an announcement: “Before Strella, studies took weeks. Now we get insights in a day — sometimes in only 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 occur on camera in real time, the AI moderator can detect when someone pauses suspiciously long — perhaps to seek the advice of ChatGPT — and flags them as potentially fraudulent. “We are fraud resistant,” Hylton said, contrasting this with traditional surveys where fraud rates could be substantial.
Solving mobile app research with persistent screen sharing technology
A significant focus of the Series A funding will probably 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 observe users navigate mobile applications in real time while the AI moderator asks about their experience.
“We are the one player out there that supports screen sharing on mobile,” Hylton said. “You know, I need to grasp what are the pain points with my app? Why do people not appear to find a way to search out the checkout flow? Well, with the intention to try this effectively, you want to see the user screen while they’re doing an interview.”
For consumer-facing firms where mobile represents the first customer interface, this capability opens entirely latest use cases. The founders noted that “several of our customers didn’t do research before” but have now built research practices around Strella since the platform finally made mobile research accessible at scale.
The platform also supports embedding traditional survey query types directly into the conversational interview, approaching what Hylton called “feature parity with a survey” while maintaining the engagement benefits of a natural conversation. Strella interviews repeatedly run 60 to 90 minutes with nearly 100% completion rates—a duration that will see 60-70% drop-off in a conventional 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 rework customer research. The founders themselves initially pursued a special 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 idea, but present in practice, no willingness to pay right away.”
Recent research suggesting firms could use language models as digital twins for customer feedback has reignited interest in that approach. But Hylton stays skeptical: “The capabilities of the LLMs as they’re today will not be adequate, for my part, to justify a standalone company. Right now you would just ask ChatGPT, ‘What would latest users of Duolingo take into consideration this ad copy?’ You can try this. Adding the standalone idea of an artificial panel is type of just putting a wrapper on that.”
Instead, Strella’s bet is that the true value lies in collecting proprietary qualitative data at scale — constructing what could turn out to be “the system of truth for all qualitative insights” inside enterprises, as Lindsey Li, Vice President at Bessemer Venture Partners, described it.
Li, who led the investment only one yr after Strella emerged from stealth, said the firm was convinced by each the technology and the team. “Strella has built highly differentiated technology that permits a continuous interview moderately than a survey,” Li said. “We heard time and time again that customers loved this product experience relative to other offerings.”
On the defensibility query that concerns many AI investors, Li emphasized product execution over patents: “We think the long game here will probably be won with one million small product decisions, all of which have to be driven by deep empathy for customer pain and an understanding of how best to handle their needs. Lydia and Priya exhibit that in spades.”
The founders point to technical depth that is difficult to duplicate. Most competitors began with adaptive surveys — text-based interfaces where users type responses and wait for the subsequent query. Some have added voice, but typically as uploaded audio clips moderately than free-flowing conversation.
“Our approach is fundamentally higher, which is the undeniable fact that it’s a free form conversation,” Hylton said. “You never have to regulate anything. You’re never typing, there isn’t any buttons, there isn’t any upload and wait for the subsequent query. It’s completely free form, and that has been a very hard product to construct. There’s an amazing amount of IP in the best way that we prompt our moderator, the best way that we run evaluation.”
The platform also improves with use, learning from each customer’s research patterns to fine-tune future interview guides and questions. “Our product gets higher for our customers as they proceed to make use of us,” Hylton said. All research accumulates in a central repository where teams can generate latest insights by chatting with the information or creating visualizations from previously unstructured qualitative feedback.
Creating latest research budgets as an alternative of just automating existing ones
Perhaps more essential than displacing existing research is expanding the full market. Krishnan said growth has been “fundamentally related to our product” creating latest research that would not have happened otherwise.
“We have expanded the use cases through which people would conduct research,” Krishnan explained. “Several of our customers didn’t do research before, have all the time desired to do research, but did not have a dedicated researcher or team at their company that was dedicated to it, and have purchased Strella to kick off and enable their research practice. That’s been really cool where we have seen this market just opening up.”
This expansion comes as enterprises face mounting pressure to enhance customer experience amid declining satisfaction scores. According to Forrester Research’s 2024 Customer Experience Index, customer experience quality has declined for 3 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 boost 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 in all three technologies poised to rework customer support by 2028, noting that “customers increasingly expect to find a way 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 each the software layer historically (~$430M) and skilled services spend on UX research, design, product strategy, etc. which is conservatively estimated to be ~$6.4B+ annually. As software on this vertical, led by Strella, becomes more powerful, we imagine the TAM will proceed to expand meaningfully.”
Making customer feedback accessible across the enterprise, not only research teams
The founders describe their mission as “democratizing access to the shopper” — making it possible for anyone in a company to grasp customer perspectives without waiting for dedicated research teams to finish months-long studies.
“Many, many, many positions within the organization would really like to get customer feedback, nevertheless it’s so hard right away,” Hylton said. With Strella, she explained, someone can “log into Strella and thru a chat, create any highlight reel that you just want and truly see customers in their very own words answering the query that you might have based on the research that is already been done.”
This video-first approach to research repositories changes organizational dynamics around customer feedback. “Then you possibly can say, ‘Okay, engineering team, we want to construct this feature. And here’s the shopper actually saying it,'” Hylton continued. “‘This is just not me. This is not politics. Here are seven customers saying they cannot find the Checkout button.’ The undeniable fact that we’re a really video-based platform really allows us to do this quickly and painlessly.”
The company has moved decisively upmarket, with contract values now typically within the five-figure range and “several six figure contracts” signed, in accordance with Krishnan. The pricing strategy reflects a premium positioning: “Our product is superb, it is very premium. We’re charging based on the worth it provides to customers,” Krishnan said, moderately than competing on cost alone.
This approach appears to be working. The company reports 100% conversion from pilot programs to paid contracts and 0 churn amongst its 40-45 customers, with month-over-month revenue growth of fifty%.
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 now have product-market fit,” Hylton said. “And now the query is execution, and we would like to rent lots of really talented people to assist us execute.”
On the product roadmap, Hylton emphasized continued deal with the participant experience as the important thing to winning the market. “Everything else is downstream of a joyful participant experience,” she said, including “the standard of insights, the quantity you might have to pay people to do the interviews, and the best way that your customers feel about an organization.”
Near-term priorities include adding visual capabilities so the AI moderator can reply to facial expressions and other nonverbal cues, and constructing more sophisticated collaboration features between human researchers and AI moderators. “Maybe you desire to listen while an AI moderator is running a call and it is advisable to find a way to leap in with specific questions,” Hylton said. “Or you desire to run an interview yourself, but you wish the moderator to be there as backup or to aid you.”
These features move toward what the industry calls “agentic AI” — systems that may act more autonomously while still collaborating with humans. The founders see this human-AI collaboration, moderately than full automation, because the sustainable path forward.
“We imagine that lots of the really strategic work that firms do will proceed to be human moderated,” Hylton said. “And you possibly can still try this 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 precise archetype of founders we’re excited to partner with for the long run — customer-obsessed, transparent, thoughtful, and singularly driven towards the home-run scenario,” she said.
The company declined to reveal specific revenue figures or valuation. With the brand 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 moderately than eliminates human judgment—where an engineering team doesn’t just read a research report, but watches seven customers struggle to search out the identical button. Where a product manager can query months of gathered interviews in seconds. Where firms don’t make a choice from speed and depth, but get each.
“The interesting a part of the business is definitely 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 corporate one.
