EPISODE · Sep 8, 2025 · 10 MIN
Catalog Attribute Extraction with Multi-Modal LLMs [Instacart]
from Snacks Weekly on Data Science · host Pan Wu
In this episode, we explore how Instacart tackled the challenge of extracting accurate product attributes at scale. We discuss different solutions—starting with SQL rules, moving to text-based ML models, and finally, Instacart’s multi-modal LLM platform, PARSE. By blending text and image data and enabling rapid configuration, PARSE demonstrates how modern AI tools can streamline data pipelines, reduce engineering overhead, and deliver better user experiences.For more details, you can refer to their published tech blog, linked here for your reference: https://tech.instacart.com/multi-modal-catalog-attribute-extraction-platform-at-instacart-b9228754a527
What this episode covers
In this episode, we explore how Instacart tackled the challenge of extracting accurate product attributes at scale. We discuss different solutions—starting with SQL rules, moving to text-based ML models, and finally, Instacart’s multi-modal LLM platform, PARSE. By blending text and image data and enabling rapid configuration, PARSE demonstrates how modern AI tools can streamline data pipelines, reduce engineering overhead, and deliver better user experiences.For more details, you can refer to their published tech blog, linked here for your reference: https://tech.instacart.com/multi-modal-catalog-attribute-extraction-platform-at-instacart-b9228754a527
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Catalog Attribute Extraction with Multi-Modal LLMs [Instacart]
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