Proven outcomes in real workflows

Using a company's entire digital footprint over time to catch every operational growth signal and compress it into one actionable, explainable score.

How a structured-finance rating agency mapped every entity, role and ownership link behind a deal from the live company graph, and verified it against SEC filings.

How a credit bureau scored 1,007 companies on 14 evidence flags drawn from their physical, digital, reputational and operational footprint.

How a fund-data provider scored its sovereign and corporate fixed-income universe on a criteria-level model built from public-institution evidence and authoritative indices.

How a credit bureau surfaced active, locatable businesses with no registry record, discovered from their digital footprint and validated to a real São Paulo address.

How a financial-data provider built four forward-looking growth signals on a live company graph, ranking companies by momentum and surfacing ones its universe had missed.

How a market-intelligence provider corrected wrong domains and addresses, captured missed acquisitions and rebrands, and mapped sprawling corporate groups of hundreds of subsidiaries to verified parents.

A Veridion pipeline replaced a manual research workflow that had limited the platform's freshness and scale.

The customer's free small-business benchmarking tool runs against Veridion's company knowledge graph, the Canadian SMB market data underneath the anonymized peer comparisons its customers see.

Source-attributed technographic data, every signal carrying its source URL, confidence score, and last-verified timestamp, supplied into the customer's global technographic offering as the deterministic foundation probabilistic providers don't deliver.

After a head-to-head evaluation against an alternative provider, the customer named Veridion's company knowledge graph as the foundational data layer underneath its company-data and ESG product expansions.

Veridion ran a specialty-extraction pipeline against Carbon Reduction Plans, sustainability reports, and ESG disclosures, returning structured emissions, target, and policy metrics resolved to the customer's company keys.

Veridion supplies geography-, industry-, and attribute-specific company datasets on demand, sized to a consulting engagement's data-collection window and delivered against the project's brief, not against a research vendor's quarterly cycle.

Veridion supplies the classification, attribute, and operational-signal depth the customer's data product surface needs, beyond what disclosure-based feeds carry.

The customer embedded Veridion's data inside its AI-driven third-party risk platform, replacing the registry-only foundation that had limited what its seven modules could see about each supplier.

Veridion extended the customer's ANZ commercial dataset with data from its company knowledge graph across both marketing-services and credit-modelling use cases.

Veridion's company knowledge graph supplies the private-company depth underneath the customer's data products: 5.4 million unique records delivered into the platform's pipelines, classified across the taxonomies its institutional clients work in, and refreshed on the news cycle's clock rather than the disclosure cycle's.

Veridion extended the customer's UK Business Information dataset with data from its company knowledge graph, deepening attribute records and surfacing companies that registry filings didn't capture.

The customer's private-markets content team built its private-company data product on Veridion's company knowledge graph, extending the platform past the listed-company universe its institutional clients had outgrown.