AI-built research on real timelines: inside Cashew's approach
The global marketing research market sits near $90B, but getting the right data is still slow and expensive. Cashew Research, based in Calgary, is changing that with AI-built research plans and surveys that collect fresh responses from real people, then analyze the results with machine learning. Think brand awareness in a specific audience, tagline testing, or quick reads on sentiment-without the usual delay.
The company's approach earned a spot in TechCrunch's Startup Battlefield 2025, where it won the Enterprise Stage at Disrupt. That visibility reflects a simple promise: faster answers, credible samples, and reports marketers can act on.
The gap Cashew fills
"You can use a large language model to do research and get answers, or hire a firm that costs a lot. Cashew is the middle ground, creating custom data instead of relying on what's already online," said co-founder and CEO Addy Graves, who has 10+ years in marketing research.
The idea came from a common client demand: real-world data in days, not weeks. For years, that timeline wasn't realistic without sacrificing quality. With AI, the workflow finally compresses while sticking to best practices and clear, decision-ready reporting.
How Cashew works
- Create a research plan and survey based on proven methods.
- Recruit real participants in the audience you care about.
- Use AI to summarize open-ends, clean the data, and surface patterns.
- Deliver simple, shareable outputs that teams can use right away.
It's built for practical needs: brand lift checks, message and slogan testing, concept validation, and audience insights. Every project uses newly collected data, not recycled panels or generic benchmarks.
Speed, cost, and access for growing brands
Automation cuts time and cost, which opens the door for small and mid-sized companies that couldn't justify traditional projects before. Cashew started in consumer goods-especially food and beverage-where quick reads heavily influence shelf wins and ad spend.
Importantly, this isn't full autopilot. Human researchers add the judgment calls that AI can't, which keeps quality in check. Over time, anonymized learnings from client projects feed a growing knowledge base that makes future work even sharper.
Why this matters for marketers
- Make go/no-go calls on creative with real audience feedback.
- Pressure-test messages by segment before you scale spend.
- Benchmark awareness in a target market and spot gaps quickly.
- Turn around stakeholder-ready reports without weeks of back-and-forth.
Funding, growth, and what's next
Cashew raised C$1.5M pre-seed and plans a seed round in early 2026 of up to C$5M. The focus is strengthening the product's technical foundation, expanding in the U.S., and building a strong B2B segment.
"People already buying research are a big group, but they're not the whole market if timelines aren't optimized," said Graves. "We're building a new category for marketers who need answers fast-and still need them to be right."
Use cases you can run this quarter
- Pre-launch ad and tagline testing across 2-3 audience slices.
- Regional brand awareness scans to guide local media mixes.
- Pricing and value perception reads to align offer strategy.
- Competitor message mapping to sharpen positioning.
Further reading and next steps
For context on Cashew's win, see TechCrunch's Startup Battlefield coverage at TechCrunch Disrupt. If you're upskilling your team on AI for marketing workflows, explore the AI Certification for Marketing Specialists at Complete AI Training.
Bottom line
If your team needs credible data on a tight timeline, Cashew's hybrid model-AI plus expert oversight-deserves a spot in your toolkit. Faster cycles, fresh samples, and decision-ready reporting give marketers the leverage to move now, not next quarter.
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