Deep Tech
Veritor doesn't just query databases. It builds a dependency graph across government registries, runs AI disambiguation in parallel, and computes transparent confidence from source authority — all in under 3 seconds.
01 — Core innovation
Standard enrichment runs all data sources in parallel. This fails when sources are interdependent — which is the reality of European government registries. Veritor's cascade engine solves this.
Most entity resolution tools query all data sources simultaneously. But European government registries are interdependent: to query the Polish tax authority (MF), you need a NIP number. To get a NIP, you need a KRS number. To get a KRS number, you need to query GLEIF first.
Running these in parallel produces incomplete results. Running them sequentially wastes time. Veritor's cascade engine builds a dependency graph at runtime and executes in optimized waves.
The engine reads connector capabilities from the database: what each registry accepts as input and what it produces as output. It then builds an execution plan:
Between waves, the engine synthesizes identifiers using country-specific rules stored in the database. For example, a Polish NIP 6920000013 becomes EU VAT PL6920000013 by prepending the country prefix. This synthesized VAT unlocks the VIES query — a connection that parallel execution would miss entirely.
The entire cascade topology is configured in the database, not hardcoded. Connector capabilities, identifier rules, country configurations, and authority weights are all stored in veritor.country_search_config. Adding a new country or registry requires database rows, not code deployment.
This means Veritor can scale from 3 countries to 27 EU countries through configuration, not engineering.
02 — AI layer
When "SAP" could be SAP SE (Germany), SAP Polska (Poland), or SAP America — AI resolves the ambiguity. Then registries confirm the answer.
Veritor runs GPT-4 and Gemini in parallel for company name validation. Both models independently assess whether a company name matches a real entity, what country it's likely in, and what identifiers might be associated. Only when both models agree does the system proceed — consensus, not single-model trust.
Most queries include a direct identifier (NIP, VAT, LEI, KRS number). The Smart Resolver detects these and bypasses the full AI pipeline, going directly to the relevant government registry. This reduces AI costs by 90% and latency by 80%. AI is reserved for genuinely ambiguous cases — name-only searches where disambiguation is required.
Neither AI nor registries alone are sufficient:
03 — Data quality
Every data point in Veritor carries full provenance. Not just "what" but "where from, how confident, when verified, and what evidence exists." This is the layer that makes Veritor audit-grade.
Every entity gets a quality score from 0 to 100 showing how much of its data comes from government registries vs estimated sources. A score of 94 means: almost everything is verified by official government sources. You always know exactly how reliable the information is.
Every data point — company name, tax number, board members, address — links directly to the government source it came from. When a compliance officer asks "where does this data come from?" you don't guess. You click the evidence link and show them the registry record.
When two registries report different company names or addresses, Veritor shows both versions and explains which one was chosen and why. No hidden decisions. Full transparency — exactly what regulators expect.
90-day timeline of every data change: when a board member was added, when the address changed, when VAT status was updated. Complete audit trail that satisfies AMLD6, DORA, and CSDD requirements.
04 — Data integrity
AI can estimate company data. Government registries can confirm it. Veritor knows the difference — and always prioritizes the source you can defend in front of a regulator.
When AI-extracted data and government registry data overlap, the registry version always takes precedence. If KRS confirms a board member's name, any AI-estimated version is automatically replaced. You always get the most authoritative data available.
Incomplete records, anonymized names, and low-confidence estimates are automatically filtered out before they reach your reports. The data you see has passed quality thresholds — so you can make decisions with confidence, not caveats.
Every data point is classified into clear trust tiers: government-verified (highest — from KRS, Companies House, GLEIF), high-confidence AI (cross-validated against multiple sources), or pending confirmation (awaiting registry verification). You always know what's certain and what's estimated.
05 — Relationship intelligence
Veritor doesn't just verify companies — it maps the people behind them. Cross-company person identity resolution reveals hidden connections, shared board members, and ownership networks.
The same person often appears across multiple companies — as a board member here, a shareholder there, a beneficial owner elsewhere. Veritor resolves them to a single identity and shows you the full picture: every company they're connected to, in every jurisdiction.
See company-person relationships as an interactive network graph. Companies as nodes, people as connections, with role labels (board member, shareholder, UBO). Click any person to see their full profile. Switch between graph and table views.
Person networks reveal what flat company data can't: a politically exposed person on the board, a sanctioned individual connected through a subsidiary, shared directors between your client and their competitor, or beneficial ownership chains through layered corporate structures.
One registry unlocks the next. GLEIF discovers an identifier that opens KRS, which produces a tax number for the Ministry of Finance. 10+ registries, connected intelligently in dependency order.
Every field links to its government source. Quality scores tell you how reliable each company profile is. When an auditor asks for evidence — you have it for every single data point.
Government registry data always takes priority over AI estimates. Low-quality records are automatically filtered. You only see data that meets compliance-grade quality thresholds.
See who's behind every company. Board members, shareholders, and beneficial owners mapped across entities. Hidden connections between companies surfaced through shared people.
When a company name is ambiguous, dual AI models resolve it independently. Only when both agree does the system proceed. Then government registries confirm the answer.
Deep coverage in Poland, UK, and US today. Germany, France, Italy, Spain, Netherlands, Czech Republic, and Sweden documented for expansion. 70+ countries via global registries.
07 — How we compare
Veritor is fundamentally different from existing entity data providers. Here's a technical comparison.
| Capability | Veritor | ZoomInfo | Clearbit | LexisNexis |
|---|---|---|---|---|
| Government registry integration | Direct, real-time | None | None | Limited |
| Cascade enrichment | Multi-wave, dependency-aware | Parallel only | Parallel only | Parallel only |
| AI disambiguation | Dual-LLM consensus | Proprietary | Basic | Proprietary |
| Confidence attribution | Per-source authority | Opaque | Opaque | Partial |
| EU/CEE coverage | Deep (PL, UK, EU-wide) | Weak | Very weak | Moderate |
| Data acquisition cost | Free (gov APIs) | Licensed data | Licensed data | Premium licensed |
| Country extensibility | DB config only | Engineering | Engineering | Engineering |
| Identifier synthesis | Cross-registry | None | None | None |
| Audit trail / evidence links | Every field, live | None | None | Partial |
| Person network / relationships | Cross-company, live | None | None | Partial |
| Beneficial ownership (UBO) | Gov registry verified | None | None | Partial |
08 — Scale
Veritor is production-grade infrastructure built over 1M+ lines of code. Designed from day one as a standalone, embeddable platform.
Early access API, dedicated integration support, and full technical documentation.