Stetos.co

Insight infrastructure. Listen at scale.

YC ApplicationArtificial IntelligenceUser Experience

▲ 68 votes10 commentsLaunched May 8, 2026

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Deploy AI agents to conduct qualitative interviews at scale. Turn thousands of conversations into actionable insights instantly. Engage your users with natural conversations and action them through dynamic outcomes. End to end conversations on voice and chat that allow you to understand even what you didn't knew you needed to understand.

AI Analysis

📝 Summary

Stetos.co is an insight infrastructure platform enabling deployment of AI agents for qualitative interviews at scale via voice and chat. Core features include natural conversations, dynamic outcomes based on user responses, and instant transformation of thousands of dialogues into actionable insights. It solves key pain points like the high time/cost of manual interviews, limited scalability in traditional UX research, and inability to uncover unexpected user needs. USP is end-to-end AI-driven engagement that listens at scale to reveal insights users didn't know they needed. Overall value proposition: deliver deep, instant understanding to inform product and business decisions efficiently.

📈 Market Timing

In 2025-2026, conversational AI and LLM technologies have reached sufficient maturity for natural interactions at scale, aligning with rising enterprise demand for automated, cost-effective qualitative research amid economic pressures to optimize user understanding without large teams. Digital transformation and AI adoption trends in SaaS further support this. Policy environments are increasingly AI-friendly despite regulation. It is a good time as tech capabilities meet pent-up needs for 'listening at scale'. Excellent Timing.

✅ Feasibility

Technical difficulty is moderate to high, relying on advanced LLMs for natural dialogue management, insight synthesis, and multi-channel (voice/chat) support. Dev/operation costs are elevated due to AI compute at scale. Supply chain risks low but compliance risks high around data privacy and consent in user interviews (e.g. GDPR). With strong AI team fit and cloud scalability, potential is good. Overall rating: High, supported by current AI tooling maturity.

🎯 Target Market

Main target segments: UX researchers, product managers, and insight teams in SaaS/tech startups and mid-to-large enterprises. Industries focus on digital products needing user feedback. Geographic distribution: global with emphasis on US/Europe innovation hubs. Estimated market size not specified in sources; qualitative insights tools represent a growing segment with strong demand. Core pain points: scaling qualitative interviews and deriving instant actionable insights. Potential willingness to pay: high for tools replacing manual processes.

⚔️ Competition

Medium. Direct competitors: 1. Remesh.ai (remesh.ai) - real-time AI qualitative research. 2. Outset.ai (outset.ai) - AI-moderated user interviews. 3. UserTesting (usertesting.com) - on-demand user insights platform. 4. Dovetail (dovetail.com) - research repository with AI analysis. Advantages: focus on autonomous AI agents for voice/chat at true scale with dynamic outcomes and unknown insight discovery. Disadvantages: newer player may have less brand trust, fewer integrations, and unproven accuracy vs established platforms with broader feature sets and enterprise compliance.

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