According to TechCrunch, Cashew Research is a Calgary-based startup targeting the $90 billion market research industry by using AI to automate the creation of research plans and surveys. Founded in 2023 by CEO Addy Graves and COO Rose Wong, the company then sends these surveys to real people and uses AI to summarize the findings. Cashew won the enterprise stage pitch at TechCrunch Disrupt 2025 and was one of 200 startups chosen for the Startup Battlefield. The company has raised C$1.5 million in pre-seed funding and is planning a seed round aiming for up to $5 million in early 2026. Its initial focus is on consumer packaged goods, and it plans to expand its U.S. presence and B2B business next year.
The middle-ground proposition
Here’s the thing Cashew is selling: a spot between two extremes. On one side, you’ve got the old-school market research firms. They’re thorough, but they’re slow and, as Graves points out, “really expensive.” On the other side, you’ve got just asking an LLM like ChatGPT. That’s fast and cheap, but you’re just getting a remix of existing internet data—not fresh insights from actual humans. Cashew’s pitch is that it automates the tedious parts (design, analysis, reporting) but keeps the crucial human data collection. It’s a compelling idea, especially for small and medium brands priced out of the traditional model. But is automating the “best practices” of researchers really that simple?
The real hurdles and risks
Look, the ambition is clear. But I think the challenges are massive. First, survey design is a dark art. Ask a question slightly the wrong way and you bias the entire result. Can an AI truly replicate the nuanced understanding of a seasoned researcher to avoid these pitfalls? Second, there’s the panel. Cashew “sends the survey to real people,” but who are they? The quality and representativeness of the respondent panel is everything in market research. Building and maintaining a reliable, diverse panel is astronomically expensive and difficult—it’s the core asset and core cost of any research firm. If Cashew is drastically cheaper, where are the corners being cut? Is it panel quality, or is the automation just that good? We don’t know yet.
The long-game data moat
The most interesting part of their strategy might be the long-term play. They’re anonymizing all the data from client projects and stuffing it into a proprietary database. Basically, every project they run makes their system smarter for future projects. That’s a potential data moat. It could help them benchmark results faster or spot trends. But it also raises big questions about data ownership and privacy. Clients are presumably paying for insights; are they also inadvertently feeding Cashew’s competitive advantage? And in a world increasingly wary of data usage, that anonymization process has to be bulletproof.
Final thoughts
So, can AI truly democratize market research? Cashew is betting yes. The funding and the Disrupt win suggest investors see the potential. Graves’s experience is a point in their favor—she’s not just a tech founder chasing a trend; she’s solving a pain point she lived. But the market research industry is entrenched for a reason. Clients pay for trust and reliability. Cashew has to prove its automated, hybrid model can deliver that same level of confidence. If they can crack the panel quality and survey integrity problems, they might just create that “new category” they’re talking about. If not, they’ll be another AI tool in a very crowded marketing stack. It’s a high-stakes experiment, and the real-world data, ironically, is still coming in.
