Build Real-Time GenAI Product Recs that Boost Cart Size

Retail is one of the most obvious industries for generative AI to make a big impact. Leveraging Gen AI with huge data sets in real-time opens up a wide range of highly nuanced and personalized customer interactions.

Combining user behavior data and vector embeddings is how developers serve up relevant, personalized suggestions in real-time. This livestream will reveal the building blocks of creating instant recommendations with GenAI, and show you how vector search enables this kind of precision and speed when building retail and e-commerce applications.

During this session, you’ll learn to:
--Drive additional product sales and views with Gen AI-driven recommendations.
--How to generate vector embeddings for your product data set.
--Work vector search into your e-commerce channel.

LIVESTREAM RESOURCES:

Rethinking Retail Data Architecture for the AI Era: https://dtsx.io/3IVH7gG
Free Astra Account: https://dtsx.io/3GMdpKB
GitHub: Ecommerce https://dtsx.io/417Fz9D
GitHub: Hugging Face Embeddings: https://dtsx.io/45ewsGB
Blog: GenAI in Retail: https://dtsx.io/3IDNKnT

Additional Resources:
DataStax Developer Hub: https://dtsx.io/devhub
DataStax Blog: https://dtsx.io/howto
Try Langflow: https://dtsx.io/trylangflow
Try Astra DB: https://dtsx.io/40kQpI6
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