How Walmart Uses GenAI to Process Claims Faster and Cut Costs? Ft. Gagandeep Singh (Ex- Walmart)
In the latest episode of our AI monetization Podcast, our Co-founder and host, Binny Mathews, converses with Gagandeep Singh, a former Senior Manager at Walmart, to explore the practical applications of AI in enterprise settings. Gagandeep unveils a case study where his team used BERT models to revolutionize auto subrogation claims processing, achieving an impressive 40-90% boost in productivity and saving millions. He offers a behind-the-scenes look at the challenges of implementing AI in large corporations, from fine-tuning models to overcoming latency issues and hallucinations.
The conversation explores cutting-edge AI trends like multi-agent frameworks and the industry's progress towards AGI. Gagandeep provides valuable insights into team composition, upskilling strategies, and staying current with AI advancements, making this a must-listen for anyone interested in the practical applications of AI in business.
For more details on this episode, visit our dedicated podcast page - https://bit.ly/4024cEW
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TIMESTAMP
00:00 Introduction
01:55 Claims Processing at Walmart
08:22 Auto Subrogation Claims Project
14:18 Technical Details of the AI Implementation
27:00 Business Outcomes and Benefits
28:46 Challenges in Deploying LLMs
37:29 Team Structure & Upskilling in Data Science
43:25 Future Trends in AI
45:35 Applicability of Agent Frameworks
47:25 Cost-effectiveness of New AI Models
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