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 global e-commerce and cloud-services company scored ~69,000 suppliers on four ESG frameworks, entirely from public evidence in the company knowledge graph.

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 an insurance data and analytics provider resolved a registry's nameless companies to their real businesses in the company knowledge graph, then classified and located each one.

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 sanctions-intelligence provider discovered 220,000+ companies in a dual-use sector, profiled them, and layered on news and sanctions monitoring to flag exposure early.

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.

How a commercial insurer scored 200 SMEs on seven layers of public evidence (hazard flags, certifications, building intelligence and imagery), each one auditable to its source.

How a commercial-property insurer got a per-building rebuild band where every multiplier is sourced and stress-testable, decomposed across region, heritage and live occupancy.

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

Veridion's location graph supplies the facility-level coverage, type classification, and source-attributed positioning the customer's physical climate-risk models need to resolve exposure at the building level rather than at the HQ.

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.

The carrier's Global Data & Analytics function licenses Veridion's company knowledge graph as a data layer underneath its commercial-underwriting and specialty-lines workflows, adding the operational depth that registry-rooted feeds don't carry across a global commercial book.

Veridion's company knowledge graph sits underneath the customer's autonomous sourcing platform, supplying the firmographic, classification, and operational depth its enterprise customers see when the platform surfaces qualified suppliers for tail-spend RFx workflows.

Veridion's ESG data layer extended the customer's underwriting view across the 80% of its commercial book that ratings agencies don't cover, and produced explainable scores its reinsurer endorsed.

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's Match & Enrich layer now sits at the front of the customer's small-business commercial workflow, validating and classifying every applicant against a weekly-refreshed company knowledge graph instead of registry data alone.

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