Veridion Review 2026

Key takeaways

• Veridion covers 80M+ companies globally with 60+ data points per profile, including granular product/service data, multi-location tracking, certifications, ESG signals, and technology stacks
• Data freshness is a genuine differentiator -- profiles are updated weekly, sourced directly from company websites, social media, and press rather than static registry databases
• Two core APIs: a Complex Search API for discovery (filter by products, industry, location, size, certifications) and a Match & Enrich API for enriching existing records with full company profiles
• Scout, a natural-language supplier discovery tool, is in early access and adds a no-code interface on top of the underlying data
• Pricing is custom and enterprise-oriented; no self-serve free tier for production use, though a startup program exists for early-stage companies
• Best fit for procurement teams, commercial insurers, supply chain intelligence platforms, and market intelligence teams -- not a fit for individual sales reps or small teams needing a simple contact database

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Veridion (formerly operating under the Soleadify brand) is a business data platform built around one core idea: company data should reflect what a business actually does right now, not what it filed with a registry two years ago. The company crawls company websites, social media profiles, and press sources continuously, then uses AI to extract and structure that raw content into clean, queryable company profiles. The result is a dataset covering over 80 million companies worldwide, each with more than 60 data points ranging from standard firmographics to granular product catalogs, certifications, ESG commitments, and technology stacks.

The platform targets a specific kind of buyer: organizations that need to make automated, data-driven decisions about businesses at scale. That means procurement teams trying to source suppliers for niche components, commercial insurance underwriters who need to classify a business accurately before binding a policy, supply chain risk teams monitoring third-party exposure, and market intelligence analysts tracking competitive landscapes. Veridion is not a CRM enrichment tool for sales reps -- it's infrastructure for decision automation, delivered primarily through API.

Customers listed on the site include Everstream Analytics (supply chain risk), Exiger (third-party risk management), and Experian, which gives a reasonable sense of the buyer profile: data-intensive organizations that embed external data into their own products or workflows rather than using a dashboard to look up individual companies.

Key features

Complex Search API

This is the main discovery engine. You can query the dataset using a combination of filters: company name, industry, keywords, negative keywords, employee size, revenue range, products and services, location (country, region, city), certifications, and supplier type (manufacturer, distributor, service provider, etc.). The filter syntax supports boolean logic -- AND/OR operators with nested operands -- which means you can write genuinely specific queries. The example on the site shows a search for aerospace cockpit assembly manufacturers that produce printed circuit boards and offer turnkey contract manufacturing. That kind of multi-dimensional product search is where Veridion separates itself from traditional firmographic databases that only classify companies by SIC or NAICS codes.

• Supports match_expression filters with configurable strictness levels (1-5 scale)
• Returns paginated results with full company profiles including all 60+ data points
• Product matches include source context: the URL, headline, and content snippet that triggered the match, so you can verify why a company was returned

Match & Enrich API

Feed in partial company information -- a name, a website URL, a phone number, an address -- and Veridion returns a full company profile. This is the data enrichment use case: you have a list of suppliers or prospects with incomplete records, and you want to fill in the gaps. The API handles fuzzy matching, so it can resolve "Sanmina Corp" to the correct entity even if the input doesn't exactly match the canonical company name.

• Returns legal names, commercial names, all known locations, employee count, revenue, industry classifications, social profiles, technologies, and more
• Confidence scores are available per data point, which matters when you're making automated decisions and need to know how reliable a given field is
• Useful for golden record creation -- consolidating multiple data sources into a single authoritative company record

Product and service data

This is probably the most distinctive part of the dataset. Rather than just classifying companies by industry code, Veridion extracts the actual products and services a company offers from its website content. The sample API response shows business_tags_generated fields like "Printed Circuit Board Assembly", "Defense & Aerospace Manufacturing", "Precision Machining" -- these are derived from crawled content, not self-reported categories. For procurement teams sourcing niche components, this is the difference between finding 50 relevant suppliers and finding 5,000 irrelevant ones.

Multi-classification support

Each company profile includes classifications across multiple taxonomies simultaneously: NAICS 2022, NACE Rev2, SIC, ISIC v4, NCCI codes, IBC insurance codes, and Veridion's own SICS taxonomy. For insurance underwriters who need to classify a business for rating purposes, having all of these in a single API response is genuinely useful -- you don't have to run separate lookups or maintain your own crosswalk tables.

Location data

Company profiles include all known locations, not just headquarters. The Sanmina example in the API documentation shows 55 locations across the US, Mexico, India, Brazil, Canada, and France, each with street address, city, region, country, and lat/long coordinates. For supply chain risk teams that need to know where a supplier's manufacturing facilities actually are (not just where they're incorporated), this multi-location coverage matters.

ESG data

Veridion extracts ESG-related signals from company websites and public sources: sustainability policies, certifications (ISO 14001, etc.), commitments, and practices. This is positioned for procurement teams that need to screen suppliers against ESG criteria and for investors doing portfolio-level ESG analysis. The depth here is harder to verify without direct access, but the data model supports it.

Technology stack detection

Company profiles include detected technologies -- CMS platforms, analytics tools, CRM systems, CDN providers, programming languages, and more. The Sanmina profile in the sample response lists 80+ detected technologies. This is useful for sales teams at software companies targeting specific tech stacks, and for market intelligence teams tracking technology adoption trends across industries.

Scout (natural language search)

Scout is a newer product in limited early access that puts a natural language interface on top of the underlying data. Instead of writing JSON filter queries, you describe what you're looking for in plain English and Scout translates that into a search. It's positioned for procurement professionals who need supplier discovery but don't have engineering resources to work directly with the API. The product is still early, but the concept is sound -- the hard part (the underlying data) already exists.

Who is it for

The clearest fit is procurement and supply chain teams at mid-to-large enterprises. Think a global manufacturer's sourcing team trying to find qualified suppliers for a specific component in a specific region, or a supply chain risk team that needs to monitor thousands of existing suppliers for changes in business activity, ownership, or financial health. Veridion's product-level search and weekly data refresh make it genuinely useful here in a way that a static database of company names and SIC codes wouldn't be.

Commercial insurance underwriters are another strong use case. Insurers need to accurately classify businesses before binding policies -- misclassification leads to premium leakage or mispriced risk. Veridion's multi-taxonomy classification and real-time business activity data let underwriters automate pre-fill and validation steps that would otherwise require manual research. The IBC insurance codes in the data model suggest this use case was designed in from the start, not bolted on.

Market intelligence teams at financial services firms, consulting firms, and corporate strategy functions are a third persona. If you're tracking a specific industry segment -- say, contract electronics manufacturers in Southeast Asia -- and you want to monitor which companies are entering or exiting the market, changing their product offerings, or growing their location footprint, Veridion's continuously updated dataset gives you a structured way to do that at scale.

Who should not use this: individual sales reps or small sales teams looking for contact data and email addresses. Veridion is not a ZoomInfo or Apollo competitor. The data model is oriented toward company-level intelligence, not individual contact records. Similarly, teams that need a simple no-code interface for occasional lookups will find the API-first approach a barrier -- Scout might eventually address this, but it's not there yet for general availability.

Integrations and ecosystem

Veridion's primary integration surface is its REST API, which is the expected delivery mechanism for all data. The API uses standard HTTP with API key authentication and returns JSON, so integration into existing data pipelines is straightforward for any engineering team.

Notable partner integrations listed on the site include Snowflake (data cloud platform), which means Veridion data can be accessed directly within a Snowflake environment without building a custom ETL pipeline. This is significant for enterprise data teams that already run their analytics on Snowflake. Other listed partners include Sapiens (insurance software), Capgemini (IT services and consulting), and a supplier intelligence platform (likely Jaggaer or similar, though not named explicitly).

The Datarade marketplace lists Veridion data, which means buyers can discover and license the data through that channel as well.

There's no mention of native CRM integrations (Salesforce, HubSpot), no browser extension, and no mobile app -- consistent with the platform's positioning as data infrastructure rather than a user-facing application.

Import/export: data is delivered via API response (JSON). Bulk dataset delivery options likely exist for enterprise customers but aren't prominently documented on the public site.

Pricing and value

Veridion's pricing is custom and not publicly listed. The Datarade marketplace indicates costs ranging from $0.03 per credit to $2,500 per dataset, which suggests a credit-based or volume-based model for API usage alongside flat-fee dataset licensing options. In practice, pricing is negotiated based on use case, data volume, and contract terms.

There is no self-serve free tier for production use. Veridion does run a Startup Programme for early-stage companies with legitimate use cases that require at-scale company data -- this appears to be an application-based program rather than an open free tier.

For comparison, traditional firmographic data providers like Dun & Bradstreet or Bureau van Dijk charge enterprise-level fees for global company data, often with restrictive licensing terms. Veridion's positioning suggests it competes on data freshness and product-level granularity rather than price, so it's unlikely to be the cheapest option for basic firmographic needs. For teams that specifically need product/service-level search or weekly-refresh data, the value proposition is clearer.

The lack of transparent pricing is a friction point for teams doing initial vendor evaluation -- you have to engage with sales before you can assess fit, which adds time to the buying process.

Strengths and limitations

What it does well:

• Product and service-level search is genuinely differentiated. The ability to find companies based on what they actually make or do -- not just their SIC code -- is something most firmographic databases can't match. The boolean filter syntax with configurable strictness gives technical buyers real control over precision vs. recall.
• Data freshness is a real advantage. Sourcing from live web crawls rather than static registries means the data reflects current business activity. The claim that 30% of supplier data changes annually is well-documented in procurement research, and weekly refresh cycles address this directly.
• Multi-taxonomy classification in a single API response saves significant integration work for insurance and financial services buyers who need to map companies to multiple classification systems.
• Global coverage at 80M+ companies is competitive with the major data providers, and the coverage of smaller, non-public companies (which often don't appear in financial databases) is particularly useful for procurement and SMB lending use cases.
• Confidence scores per data point let downstream systems make calibrated decisions rather than treating all data as equally reliable.

Limitations:

• No contact-level data. If your use case requires individual decision-maker names, email addresses, or direct phone numbers, Veridion doesn't cover this. The platform is company-level intelligence only.
• API-first with limited no-code access. Scout is in early access and not generally available. Teams without engineering resources will struggle to get value from the platform today.
• Opaque pricing. No public pricing tiers means every evaluation requires a sales conversation. For teams comparing multiple vendors, this slows down the process.
• Verification depth varies. The data is AI-extracted from web content, which means accuracy depends on what's published on a company's website. Companies with thin or outdated web presences may have incomplete profiles. The confidence score system helps, but it doesn't eliminate the underlying limitation.

Bottom line

Veridion is a strong choice for enterprise procurement teams, commercial insurance underwriters, and supply chain intelligence platforms that need to search, discover, and enrich company data at scale -- particularly when the use case requires product-level specificity or real-time data freshness that traditional firmographic databases can't provide. The API is well-designed, the data model is genuinely deep, and the multi-taxonomy classification support saves real integration work.

Best use case in one sentence: an enterprise procurement team that needs to find qualified suppliers for a specific manufactured component across multiple geographies, then monitor those suppliers for changes in business activity, certifications, or risk signals -- all through a single API.