How DoorDash Uses LLM Juries to Build Accurate Food Metadata at Scale

Building Food Metadata with LLM Juries

We tackled the challenge of standardizing millions of unique food items by building an AI-led metadata platform. Our system uses LLM juries for high-quality evaluation, context-optimization agents to refine prompts tenfold, and distributed computing to slash processing time. This approach replaced slow human labeling, boosting accuracy by 20% while cutting costs, ensuring a superior search experience for our users.

"We found that the consensus LLM tags were about 20% more accurate than typical human-annotated labels."