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Operationalizing LLMs: From Prototype to Production

Operationalizing LLMs: From Prototype to Production

Data Phoenix
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Data Phoenix
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Thursday, August 27, 2026
10:00 AM PDT – 11:00 AM PDT · Pacific Time
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About this event

At Instacart, large language models (LLMs) play a crucial role in enhancing the grocery shopping experience and streamlining support for both customers and shoppers. Two key use cases showcase the transformative potential of AI:

  • AI-Generated Recipes: Instacart employs LLMs to create recipes based on top SEO-searched keywords, ensuring relevance in online searches and customer engagement. These AI-generated recipes are paired with visually appealing, AI-created images to further captivate users and enhance discoverability. This involves developing a complex AI recipe ingestion pipeline.

  • AI-Powered Chatbot: Instacart leverages LLMs at scale to build intelligent chatbots that address customer and shopper inquiries efficiently. By understanding context and providing accurate, conversational responses, these chatbots solve issues ranging from order updates to product guidance, reducing support friction.

Both use cases highlight how LLMs are driving innovation and operational efficiency in a fast-paced, customer-centric environment.

Speakers

Yogiraj Awati
Yogiraj Awati
Engineering Manager, Instacart
Profile

Yogiraj is a seasoned technology leader with over a decade of expertise in distributed computing, Agentic AI, and large language models (LLMs). As part of Instacart’s leadership team, he is driving the transformation of grocery shopping through cutting-edge AI solutions, digitizing customer experiences, and empowering retailers with a comprehensive suite of AI-powered offerings.

Previously, Yogiraj contributed to Amazon Web Services (AWS) as a founding member of the AWS X-Ray team, where he helped develop it into a leading observability service.

Launch partner

AgentField

AgentField is open-source infrastructure for building autonomous software factories and the AI backends that power them. It gives multi-agent systems a single control plane for orchestration, governance, and provenance - so every action your agents take is policy-checked and accountable, with no glue code and no editable logs. Apache 2.0, with SDKs in Python, TypeScript, and Go.

Partners