aiGalen Guan

Cookiy AI: The First Agentic AI User Research Platform

In the landscape of AI startups, few manage to carve out a genuinely new category. Cookiy AI, a Silicon Valley-based company, has done exactly that — positioning itself as the world's first Agentic AI User Researcher. This isn't just another AI summarization tool or chatbot wrapper; it's a platform that promises to completely reimagine how user research is conducted.

What is Cookiy AI?

Cookiy AI describes itself as an Agentic Research Platform — a system that autonomously conducts end-to-end user interviews, from participant recruitment to insight synthesis. The bold claim: "Talk to 100 users. Get insights by tomorrow."

The platform's key metrics are striking:

  • 100+ interviews in a single day
  • ~4 hours from research goal to actionable insights
  • Access to 170 million possible respondents worldwide

The Problem: A Structural Crisis in Qualitative Research

Traditional user research faces a fundamental scalability problem. Expert researchers are expensive, time is limited, and the "individual brilliance" of skilled interviewers cannot be easily replicated. Companies either:

  • Conduct small-sample studies that lack statistical power
  • Rely on surveys (losing the depth of qualitative conversation)
  • Scale too fast and lose research quality entirely

Cookiy AI's mission statement addresses this directly: "Solving the Structural Crisis in Qualitative Research." Their core thesis is that AI shouldn't replace researchers — it should amplify their capabilities by handling the operational heavy lifting.

How It Works: Four Simple Steps

The Cookiy platform operates in four stages:

  1. Describe Your Goal (~5 min): The researcher inputs what they want to learn. Cookiy asks clarifying questions and generates a complete, expert-level discussion guide instantly.

  2. Automated Recruitment & Scheduling: Cookiy handles participant sourcing and interview scheduling at scale.

  3. AI-Moderated Interviews: This is where the magic happens. The AI conducts video interviews while simultaneously:

    • Detecting hesitation and digging deeper automatically (Smart follow-ups)
    • Analyzing real-time emotional signals (sentiment tracking throughout the conversation)
    • Enabling researchers to watch live or inject follow-up topics mid-session

  4. Insight Delivery: Within hours, researchers receive:

    • Written findings, structured and ranked
    • Stakeholder-ready presentations
    • Automatically clipped video moments that matter

What Makes Cookiy Different?

The company is notably "opinionated" about its approach. Their five core principles:

  1. AI should amplify researchers, not replace them. The platform is designed as a force multiplier for human expertise.

  2. Methodology > Models. Cookiy emphasizes that good research is about rigorous methodology, not just powerful language models.

  3. Good questions are scarcer than good answers. The quality of insights depends on the questions asked — a principle deeply embedded in their discussion guide generation.

  4. True insight comes from judgment. AI can surface patterns, but human judgment remains essential for interpretation.

  5. Research is an organizational asset. Insights should be captured, organized, and reusable — not lost in individual notebooks.

Technical Differentiation: Agentic Architecture

Cookiy has released Cookiy Skill & CLI as open-source tools, making their research capabilities available to AI agents. Their platform is compatible with leading AI agent platforms:

  • Claude
  • OpenAI
  • Cursor
  • Manus
  • OpenClaw

This "agentic" approach means any AI assistant can now run end-to-end user research pipelines — participants, interviews, surveys, and insights — all orchestrated by the AI itself.

Real Research in the Wild

Perhaps most impressively, Cookiy practices what they preach. Their "Discoveries" page showcases real research studies conducted using their own platform:

  • "They see the storm. They can't afford umbrellas" — How workers view AI's impact on their jobs
  • "Work anywhere. Rest nowhere" — Bay Area professionals between workload, housing costs, and flexible work dreams
  • "Apple owns the ecosystem. Not the enthusiasm" — 50 loyal users on Apple's CEO transition
  • "Gen Z Dating Preferences" — How young adults decide who to meet
  • "Reviews shape purchases. No one trusts reviews" — 21 shoppers on the credibility collapse of online reviews

These aren't hypothetical use cases — they're published research demonstrating the platform's real-world capability.

The Founder: Davin

Market Positioning

The company is led by Davin (Chinese name: 王大力 — Dali Wang), who is described as a "renowned builder and growth visionary" with a career spent "scaling world-class platforms and pioneering new categories in AI and growth."

Interestingly, the GitHub profile for cookiy shows Dali Wang based in Beijing, with the bio "May the force be with you" — suggesting possible ties to China's tech ecosystem alongside the Silicon Valley headquarters.

Market Implications

Cookiy AI represents a fascinating intersection of several trends:

  1. Agentic AI: Beyond chatbots and copilots, we're now seeing AI agents that can autonomously execute complex workflows.

  2. Research democratization: Smaller teams can now access research capabilities previously reserved for large enterprises with dedicated research teams.

  3. Quality-speed tradeoff elimination: The "~4 hours to insights" claim challenges the assumption that fast research must mean shallow research.

  4. Voice as UI: Cookiy's focus on video interviews and real-time emotional analysis positions voice/video as a critical interface for AI.

Challenges Ahead

As with any early-stage startup in a novel category, Cookiy faces real challenges:

  • Trust: Can researchers trust AI-generated insights the way they trust human interviewers?
  • Methodological rigor: Qualitative research has established best practices — how does AI moderation affect these?
  • Ethical considerations: What are the boundaries of AI-conducted interviews versus human-led research?
  • Market education: Many potential customers may not even know this category exists.

Conclusion

Cookiy AI is a compelling case study in category creation. By positioning themselves at the intersection of AI agents, user research, and voice interfaces, they've identified a genuine pain point — the inability to scale qualitative research — and built a platform to address it.

Whether they can deliver on their ambitious promise of "100 interviews, insights by tomorrow" at enterprise quality remains to be seen. But they have, at minimum, opened a door that many in the research community will be watching closely.

Have you tried Cookiy AI or similar agentic research tools? I'd love to hear about your experience in the comments.

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