Qloo, a company that provides taste intelligence for AI agents, named Undertow the winner of its Global Agentic Hackathon, which drew nearly 3,000 developers worldwide. Investor Jason Calacanis pledged $25,000 to Undertow during the November 5 finals on This Week in Startups. Engineer Abdal Hassani built Undertow with Qloo's taste data to create county-level profiles and blend them with public polling. Its combined forecast picked Democrat Josh Turek in Iowa's Senate race, while a polling-only forecast narrowly favoured Republican Ashley Hinson. Turek won. In Hassani's preliminary review of 33 Senate races, the combined forecast called 32 winners, against 31 for polling alone. Calacanis said he sees uses beyond elections, such as deciding where to spend ad budgets or which cities to tour.

Kearney taps Qloo's cultural AI to decode what consumers want. Key takeaways. * Off-road enthusiasts and mainstream EV buyers overlap across outdoor brands, entertainment, media and lifestyle interests. * The research points to white space for rugged, utility-focused EVs in the $40,000-$60,000 segment. * Cross-domain cultural signals surface relationships that vehicle ownership data and demographics overlook. * Automakers can use cross-category consumer intelligence earlier in product development, positioning and market entry. NEW YORK, October 27, 2026 - Qloo, the AI company powering cultural intelligence and taste-based inference, today highlighted new research conducted with global management consulting firm Kearney's Product Excellence and Renewal Lab (PERLab), demonstrating how artificial intelligence can reveal overlooked market opportunities by understanding the connections between consumer interests, lifestyles, and preferences. The research, published by Kearney in its report Can rising fuel costs and a love for the outdoors open the market for off-road EVs?, combines Kearney's automotive and product strategy expertise with Qloo's proprietary Taste AI platform to examine an emerging question for automakers: could traditional off-road enthusiasts represent a significant opportunity for the next generation of electric vehicles? The findings challenge conventional assumptions about who the next EV customer might be. Using Qloo's cross-domain taste intelligence, researchers analyzed the cultural affinities associated with three distinct audiences: traditional off-road enthusiasts, mainstream electric vehicle buyers, and a Rivian-associated audience. The analysis revealed that traditional off-road enthusiasts and mainstream EV buyers share substantially more cultural interests than conventional automotive segmentation might suggest. Among the findings: * Unexpected audience convergence: Off-road enthusiasts and mainstream EV buyers exhibited meaningful overlap across outdoor brands, entertainment, media, and lifestyle interests, challenging assumptions that these audiences occupy fundamentally different cultural worlds. * An underserved market opportunity: The research identified potential white space for rugged, utility-focused electric vehicles in the $40,000-$60,000 segment, where mainstream affordability and credible off-road capabilities have yet to converge at scale. * Cultural signals beyond conventional demographics: Qloo's AI revealed relationships across brands, media, fashion, dining, retail, and travel that traditional vehicle ownership data or demographic analysis may overlook. * Implications for product development: The findings suggest automakers can use cross-category consumer intelligence to inform product positioning, feature prioritization, and market-entry strategies earlier in the development process. The study also found that the Rivian-associated audience exhibits a more design-oriented interpretation of outdoor adventure, while mainstream EV buyers share significant affinities with traditional off-road enthusiasts - suggesting room for differentiated products serving distinct consumer identities. Understanding what consumers will value next. Unlike traditional approaches that rely primarily on demographics, surveys, or historical purchasing behavior, Qloo models relationships among cultural entities and consumer preferences across categories. Its privacy-first architecture enables organizations to explore affinities and make inferences without relying on personally identifiable information. The approach provides a complementary intelligence layer for understanding consumers and evaluating new market opportunities. A new intelligence layer for product and market strategy. The Kearney research illustrates a broader application of Qloo's technology: using cross-domain AI inference to inform strategic decisions well beyond conventional personalization and recommendation systems. By mapping relationships among culture, preference, and place, Qloo enables organizations to explore how interests in one domain may relate to opportunities in another. These capabilities have applications across automotive, commerce, financial services, travel, hospitality, and the emerging generation of AI-powered agents - where understanding relevance and preference is increasingly important to making useful real-world decisions. The research underscores how AI-powered cultural intelligence can complement traditional market research, helping businesses identify unexpected customer adjacencies, evaluate product concepts, and better understand what consumers value before making significant strategic investments. The Q3 2026 study compared interest-defined audience cohorts, including a Rivian-affinity cohort rather than verified owners. Findings are directional and do not establish purchase intent or market size. About Kearney. Kearney is a leading global management consulting firm. Its Product Excellence and Renewal Lab (PERLab) helps organizations improve product competitiveness through product strategy, design, engineering, and innovation. Learn more at www.kearney.com. What's next? Reach out to discover how Qloo can elevate your business through personalized solutions tailored to your unique needs.