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Vody | August Retail Tech Startup Of The Month

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Manage episode 502369519 series 2106196
Content provided by Omni Talk Retail. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Omni Talk Retail or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
AWS’s Daniele Stroppa, Worldwide Technical Lead for AWS partners in retail, joins us to announce August’s retail tech startup of the month: Vody. Daniele breaks down how Vody makes data ready for AI and AI agents through their intelligent data infrastructure solutions. Unlike typical approaches that tackle product discoverability with chatbots or search improvements, Vody addresses the challenge at its foundation – the data itself. Their sophisticated system transforms messy product catalogs into AI-optimized data using state-of-the-art multimodal large language models specifically fine-tuned for retail. 🔑 Topics covered: Why Vody stands out with their data-first approach to AI readiness How they structure data from diverse sources (PDFs, spreadsheets, etc.) and inject real-world context The impressive 10% conversion rate improvements their customers are seeing Why tackling data quality at the foundation benefits search, recommendations, marketing, and merchandising How Vody works with existing customer data without expensive migrations From understanding trends to identifying perfect Father’s Day gifts, Vody’s AI-optimized data helps retailers stay one step ahead of their customers while driving real business results across multiple areas of their operations. 🎧 Don’t forget to like, comment, and subscribe for more retail tech insights and to be the first, each month, to find out who wins retail tech startup of the month! Music by hooksounds.com #retailtech #AI #ecommerce #dataoptimization #omnitalk #retailinnovation #vody #retailpodcast #aws #productdiscoverability Sponsored Content
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1545 episodes

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Manage episode 502369519 series 2106196
Content provided by Omni Talk Retail. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Omni Talk Retail or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
AWS’s Daniele Stroppa, Worldwide Technical Lead for AWS partners in retail, joins us to announce August’s retail tech startup of the month: Vody. Daniele breaks down how Vody makes data ready for AI and AI agents through their intelligent data infrastructure solutions. Unlike typical approaches that tackle product discoverability with chatbots or search improvements, Vody addresses the challenge at its foundation – the data itself. Their sophisticated system transforms messy product catalogs into AI-optimized data using state-of-the-art multimodal large language models specifically fine-tuned for retail. 🔑 Topics covered: Why Vody stands out with their data-first approach to AI readiness How they structure data from diverse sources (PDFs, spreadsheets, etc.) and inject real-world context The impressive 10% conversion rate improvements their customers are seeing Why tackling data quality at the foundation benefits search, recommendations, marketing, and merchandising How Vody works with existing customer data without expensive migrations From understanding trends to identifying perfect Father’s Day gifts, Vody’s AI-optimized data helps retailers stay one step ahead of their customers while driving real business results across multiple areas of their operations. 🎧 Don’t forget to like, comment, and subscribe for more retail tech insights and to be the first, each month, to find out who wins retail tech startup of the month! Music by hooksounds.com #retailtech #AI #ecommerce #dataoptimization #omnitalk #retailinnovation #vody #retailpodcast #aws #productdiscoverability Sponsored Content
  continue reading

1545 episodes

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