# Enterprise AI: Research to Product | Data Brew | Episode 43

Page: https://stenobird.com/podcast/data-brew-by-databricks/enterprise-ai-research-to-product-data-brew-episode-43
Text version: https://stenobird.com/podcast/data-brew-by-databricks/enterprise-ai-research-to-product-data-brew-episode-43.md
Podcast: [Data Brew by Databricks](https://stenobird.com/podcast/data-brew-by-databricks)
Published: 2025-04-10T15:00:00+00:00
Episode link: https://www.buzzsprout.com/1370119/episodes/16873712-enterprise-ai-research-to-product-data-brew-episode-43.mp3
Audio file: https://www.buzzsprout.com/1370119/episodes/16873712-enterprise-ai-research-to-product-data-brew-episode-43.mp3
Processing state: processed
JSON: https://stenobird.com/v1/public/podcasts/data-brew-by-databricks/episodes/enterprise-ai-research-to-product-data-brew-episode-43
Duration seconds: 2283

## Resource

In this episode, Dipendra Kumar, Staff Research Scientist, and Alnur Ali, Staff Software Engineer at Databricks, discuss the challenges of applying AI in enterprise environments and the tools being developed to bridge the gap between research and real-world deployment. Highlights include: - The challenges of real-world AI—messy data, security, and scalability. - Why enterprises need high-accuracy, fine-tuned models over generic AI APIs. - How QuickFix learns from user edits to improve AI-dri...

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## Transcript

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