Culture Shift | Qloo Agentic Hackathon

Inspiration

Product launches are shaped by more than features and functionality. Cultural context influences how people discover brands, form affinities, and interpret positioning across different markets.

We built CultureShift to explore how cultural intelligence can help founders challenge assumptions before taking a product to market.

Our goal is to turn cultural research into a practical decision-making workflow that connects market research, positioning analysis, strategic alternatives, and evidence review.

What It Does

CultureShift is a cultural intelligence platform designed to help founders and product teams investigate product positioning across markets.

Its core workflow brings together:

Cultural Research: Explore relevant cultural entities and available affinity signals through Qloo's Taste AI.
Cross-Market Analysis: Compare research findings across selected markets.
Cultural Positioning: Develop and examine alternative ways to position a product.
Strategic Risk Analysis: Identify assumptions, potential risks, and areas requiring further validation.
Evidence-Aware Recommendations: Separate retrieved evidence from interpretations and unverified hypotheses.
Exportable Results: Present research findings and strategic recommendations in a structured report.

The objective is not to predict guaranteed launch success. It is to help teams make better-informed decisions about how they position products for different cultural contexts.

How We Built It

We developed CultureShift as an AI-powered research and strategy application, combining a product briefing workflow, cultural research, analytical reasoning, and a results interface.

Qloo's Taste AI API provides the cultural intelligence layer for supported entity and affinity research. The application uses the resulting information as context for interpreting positioning opportunities and comparing markets.

Our intended agentic workflow separates market analysis, cultural research, adversarial review, strategy development, and evidence verification into distinct responsibilities.

We designed the workflow around an important principle: retrieved data, AI-generated interpretations, and unverified hypotheses should not be treated as interchangeable.

Challenges We Ran Into

One of the central challenges was translating cultural signals into actionable product strategy without overstating what the data proves.

A cultural association is not automatically evidence of purchase intent, product-market fit, or a successful launch. Cross-market comparisons also require careful attention to differences in available evidence and research context.

We therefore focused on making the relationship between research, interpretation, assumptions, and recommendations clear.

Integrating live API research into a coherent multi-stage analytical workflow also requires careful handling of authentication, response validation, missing data, and failures.

Accomplishments That We're Proud Of

We brought the idea of cultural intelligence into a practical product-launch workflow rather than treating it as a standalone search tool.

CultureShift connects cultural research with positioning analysis, market comparison, strategic alternatives, risk assessment, and structured results.

We are especially proud of the evidence-aware direction of the product: recommendations should be useful, but their supporting evidence and limitations should remain visible.

What We Learned

We learned that an effective AI research product needs more than a powerful model or an attractive interface.

Reliable source data, clear analytical responsibilities, transparent uncertainty, and meaningful validation are essential for turning AI-generated insights into useful business decisions.

We also learned to distinguish between what a cultural intelligence API actually returns and what an AI system infers from those results.

What's Next for CultureShift

Our next steps are to strengthen the end-to-end research workflow, expand cross-market comparisons, improve evidence verification, and make strategic reports more useful for founders and product teams.

We aim to develop CultureShift into a reliable cultural intelligence workspace that helps teams investigate assumptions, design experiments, and approach new markets with greater clarity.