Most retail AI tools promise to help you sell more. Bijan Vaez started by asking a simpler question: what if the problem is the data itself?That question pulled him from early AI experiments in product photography into the unglamorous but critical work of AI-powered product catalog management. As CEO of Merch Kit (and a three-time founder and former CTO who has scaled SaaS products to millions of users), he helps large brands, marketplaces, and enterprise retailers clean, enrich, and structure their product information. The goal: make it usable across multiple channels without weeks of manual effort.This conversation is a real-world case study in applied AI for retail operations. Bijan explains why messy data is one of the biggest barriers to AI delivering value, and how solving those upstream issues makes every downstream tool, and every person using it, far more effective.He also shares how to keep pace with a field that changes every week, what trust looks like in an AI product partnership, and why the best AI systems make human work more creative, not less.🔑 What You’ll Learn in This Episode✅ How to pivot from early AI experiments into a market-sized problem✅ Why messy product data can block AI from delivering results✅ How to build AI into human workflows without replacing people✅ The role of trust and adaptability in AI product partnerships✅ Where Bijan sees the next frontier for connected AI systems🔗 Resources & Links🤝 Connect with Bijan: https://www.linkedin.com/in/bijanvaez/🛒 Learn more about MerchKit: https://www.merchkit.com/📩 Subscribe to the newsletter for more AI insights: https://manary.haus/podcast#haus👉 Have a guest in mind? Reach out to Daniel at [email protected]💬 If this episode sparked an idea for how AI could work in your own business, share it with a colleague and start the conversation!

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