AI case study

Allspice LabsSearch and data matching

Messy ingredient data broke text search, capping matches at 20%. AI semantic search now maps free-form inputs to unlock recipe imports.

Published|1 month ago

Key results

Matching Accuracy
97%

Result highlights

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The story

Context

A food technology platform serving consumers and B2B publishers that manages complex, semi-structured culinary data to power recipe discovery, pantry inventory, and automated shopping lists.

Challenge

Ingredient data is inherently messy, with variations like 'one bunch of cilantro' and 'fresh cilantro, chopped' causing deterministic text search to...

Solution
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Quotes

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The company

Allspice Labs logo

Allspice Labs

allspicelabs.com

Interactive cooking and meal planning platform for recipe publishers.

IndustrySoftware & Platforms
LocationNew York, NY, USA
Employees1-10
Founded2023

The vendor

Managed vector database for AI search, retrieval, and recommendation systems.

IndustrySoftware & Platforms
LocationNew York, NY, USA
Employees251-1K
Founded2019

Use case

Allspice Labs's Search and data matching is part of this use case:

Specialized Search
28 case studies(+111% YoY)
Proven impact?
LowModerateVery Strong
5.2Strong
3.9Moderatewithin Product Engineering

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