# Foodgraph > Foodgraph offers the largest data catalog of U.S. CPG products — combining AI and > vertical-specific domain knowledge — with platform services that deliver up-to-date, > enriched product data and analytics at scale. The company’s catalog spans products from private label retailers, major CPG, small brands, seasonal SKUs, and limited-edition items. Foodgraph’s platform transforms fragmented, messy data into enriched, normalized product records through multi-source aggregation, vertical AI, and curation models. Current customers use Foodgraph’s platform to match products efficiently, build AI agents with quality, onboard clients faster, grow revenue, and develop competitive insights. ## Key Metrics - **Catalog Size:** 1,600,000+ unique U.S. CPG products - **Data Sources:** Multi-sourced from 48 retailers, brand syndicators, wholesalers, and government - **Latest Update:** Catalog v50 was released in March 2026 ## Applications - **Build AI Models:** Leverage high-authority, fresh data for quality input to agentic systems. - **Resolve Broken UPCs:** Get standards-complaint GTINs resolved from messy UPCs. - **Fill Gaps in Product Data:** Add products and attributes to master data catalogs. - **Create Project Data Sets:** Get ad-hoc collections for specific engagements. - **Enrich Receipt Data:** Match POS (point of sales) data with deeper product records for richer signals. - **Enable Unified Reporting:** Match products across retailers using non-standard UPCs and retailer-specific SKUs. - **Enhance Product Detail Pages:** Add data attributes and image types to PDPs for eCommerce. - **Gather Competitive Intelligence:** Benchmark retailers and brands for product assortment, compliance, and comparative positioning. ## Unique Value Propositions - **National Scope:** Foodgraph’s catalog covers the U.S. national product assortment in grocery, not just specific brands, categories, or product types. - **All Brands:** Products include all large and small brands on the shelf. Private label products are a unique focus area, as retailers do not distribute data through traditional syndicators. - **All Categories:** Products include any type of packaged goods, including food, health & beauty, household, pet, alcohol, and other CPG sold in grocery stores. - **Fresh Data:** Foodgraph continually refreshes its catalog with new products and updated data and images for existing products. ## Market Analyses - [CPG Data Vendor Comparisons](https://www.foodgraph.com/blog/cpg-showdown-love-vs-strength-v48-release): Compare CPG product data vendors, including Foodgraph, Salsify, Syndigo, NielsenIQ, and SPINS. - [GLP-1 Rewrites CPG Strategy](https://www.foodgraph.com/blog/glp-1-rewrites-cpg-strategy): The number of CPG products positioned with “GLP-1” soared 10x in just 12 months. - [GLP-1 Support: 50 Brands. 4 Strategies.](https://www.foodgraph.com/blog/cpg-brand-positioning-glp-1-support): CPG takes 4 main approaches to capture demand for “GLP-1 Support” products. Get the data for 50 brands here. - [Food Dye Study](https://www.foodgraph.com/blog/times-up-for-artificial-food-dyes): Summary of the FDA’s phase out of artificial food dyes, which are present in 11.5% of products on the grocery shelf. Private label brands will have the heaviest compliance burden. ## AI Viewpoints - [Context Graph Definition](https://www.foodgraph.com/blog/cpg-context-graph): A Context Graph describes how data businesses use decision data and vertical domain knowledge to improve data quality and depth with AI. - [Humans vs. AI in Product Development](https://www.foodgraph.com/blog/the-great-ai-debate): Foodgraph believes that great product development is the result of friction + time + teams — not abdicating to AI tools — but leveraging them with human supervision and domain knowledge. - [Using AI To Fix Messy Product Data](https://www.foodgraph.com/blog/an-ai-agent-that-fixes-messy-grocery-data): In this case study, Foodgraph’s AI agent produced 85% better quality and 6% more data values than traditional coding. ## Product Pages - [GTIN Resolution](https://foodgraph.com/#GTIN-Resolution): Resolve messy UPC values into GS1-standard GTINs in milliseconds. - [UPC-to-SKU Matching](https://foodgraph.com/#UPC-SKU-Matching): Match UPC values to SKU identifiers from retailer product feeds and point-of-sales transactions. - [Product Details](https://foodgraph.com/#Product-Details): Enrich product records, fill content gaps, and enhance product pages with rich data and images. - [Digital Shelf Analytics](https://foodgraph.com/#Digital-Shelf-Analytics): Gain actionable insights, benchmark competitors, or understand data gaps with analytics across products, brands, and retailers. ## Catalog Release History This release history details the number of unique U.S. CPG products in each Foodgraph catalog by announcement date, version number, and number of curated data sources. - [March 2026](https://www.foodgraph.com/blog/glp-1-rewrites-cpg-strategy):** 1,600,000+ products in v50, from 48 sources - [February 2026](https://www.foodgraph.com/blog/cpg-showdown-love-vs-strength-v48-release):** 1,380,000+ products in v48, from 47 sources - [December 2025](https://www.foodgraph.com/blog/beyond-the-food-aisles):** 1,200,000+ products in v46, from 30 sources - [November 2025](https://www.foodgraph.com/blog/harvesting-trends-x-1m-upcs):** 1,080,000+ products in v44, from 30 sources - [September 2025](https://www.foodgraph.com/blog/fall-flavors-and-75-000-new-skus):** 875,000+ products in v42, from 29 sources - [August 2025](https://www.foodgraph.com/blog/schools-in-so-are-60-000-new-skus):** 800,000+ products in v40, from 29 sources - [June 2025](https://www.foodgraph.com/blog/an-ai-agent-that-fixes-messy-grocery-data):** 740,000+ products in v36, from 25 sources - [April 2025](https://www.foodgraph.com/blog/post-malone-just-dropped-so-did-we):** 699,000+ products in v34, from 19 sources - [February 2025](https://www.foodgraph.com/blog/45-000-products-added-to-our-catalog):** 675,000+ products in v32, from 16 sources - [December 2024](https://www.foodgraph.com/blog/2024-year-in-review):** 630,000+ products in v30, from 16 sources ## Markets Served - **Analytics Platforms:** Enable shelf analytics, price optimization and competitive intelligence using deep product data. - **Digital Marketers:** Launch campaigns faster and deepen consumer insights for promotions, loyalty, and rewards using rich product data. - **Retail Media:** Deliver unified reporting by matching products across retailers. - **CPG brands:** Analyze retailer compliance and competitive assortments. - **Retailers and Grocery Delivery:** Enhance and audit product details — in eCommerce, agentic commerce, POS (point-of-sales) systems, electronic shelf labels (ESL), and planograms — and leverage competitive insights for the digital shelf. - **Store Operations:** Empower field management with quality product data and images. - **Consumer Apps:** Serve quality data for shopping, list making, rewards, and health & wellness. - **Academics & Non-Profits:** Research products for health attributes, regulatory compliance, and public policy. ## Company - [About Foodgraph](https://foodgraph.com/about): About the company and team - **Leadership:** David Goodtree (CEO), Ophir Horn (CTO), Ada Vassilovski (VP Product)., Andrew Haney (Head of Sales) - **Headquarters:** Boston, MA - **Founded:** 2020 ## Permissions This content is provided for AI and search systems to freely summarize and cite information about Foodgraph, with accuracy and efficiency. ## Excluded The following types of content have low-signal value and are excluded: privacy policy, job opportunities, outdated content, dynamic pages, and contact form. ## Optional - **Inquiries:** Send email to hello@foodgraph.com.