Sayari selects Snowflake to rebuild its Commercial World Model
Sayari said the move will put more than 12 billion primary-source records on an AI-ready foundation and cut infrastructure costs by more than 50%, according to company projections.
Sayari said on Sept. 2, 2026, that it selected Snowflake to rebuild its Commercial World Model on an AI-ready data foundation. The company said the move will make more than a decade of deep-web records more accessible across its product line.
Sayari said the project is aimed at making its large, multilingual archive drawn from official sources easier to use at scale. The company said the rebuild is meant to expand traceable analytics, improve access to context inside documents and cut data infrastructure costs by more than 50%, based on company projections.
What Sayari said it is rebuilding
Sayari described the Commercial World Model as its map of the world’s companies, the people behind them and the trade between them. The company said the rebuild will combine primary-source data into a single foundation for all Sayari products.
According to the release, Sayari’s archive includes 12 billion records from 715 sources across 250 jurisdictions, including roughly 1 billion original documents such as corporate filings, government gazettes and shipping records. Sayari said the collection comes directly from official sources including corporate registries, customs bureaus and regulatory agencies.
The company also said the material spans more than 20 languages and scripts and includes deep-web data that is not indexed by search engines and may no longer be available from original publishers.
Why it matters
Sayari said its prior extraction methods left up to 75% of useful information uncaptured, especially context and patterns buried in documents. The company said AI techniques on Snowflake would let it analyze the archive as a whole rather than document by document.
In the release, Sayari said the rebuilt platform is intended to help customers trace ownership further, detect risk earlier and surface new classes of risk intelligence. Sayari said its customers use its products to help secure supply chains, surface sanctions-evasion and forced-labor risks, and dismantle illicit networks.
Background and context
Sayari said it has spent more than a decade building extraction pipelines for its archive. The company said the data spans more than 250 jurisdictions and is used by organizations including U.S. Customs and Border Protection, U.K. HM Revenue & Customs, Fortune 500 enterprises and thousands of professionals across more than 35 countries.
The release also said trade wars, sanctions and geopolitical tensions are reshaping global supply chains and company risk. Sayari framed the rebuild as part of its effort to turn raw records into assessed intelligence that customers can source, verify and act on.
What officials said
Jessie Abell, Sayari’s chief product officer, said Fortune 100 companies and national intelligence agencies rely on Sayari and that rebuilding on Snowflake will let the company read its archive at global scale. Abell also said Sayari has built an archive of records nobody else has, but many had been out of reach.
Jennifer Chronis, Snowflake’s vice president for U.S. public sector, said AI is only as powerful as the data behind it. Chronis said Snowflake is proud to support Sayari and help bring AI to data that has not been accessible until now.
What happens next
Sayari said its engineering team used Snowflake CoCo, Snowflake’s AI coding assistant, to accelerate the migration. The company said it plans to introduce products built on the new foundation later in 2026 that will deliver finished answers customers can trace, verify and defend.
The company’s cost savings estimate and product plans were presented in its announcement and were not independently verified in the release.
Sources
Editorial note: This article was prepared with AI assistance and includes source attribution for reader review.
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