FAQ
Common questions, direct answers.
What Apriori covers, how the organization graph is built, and how to work with us. If your question is not here, ask us directly.
What types of public records does Apriori cover?
Apriori covers public records across four layers - federal, state, local, and international. Coverage spans regulatory filings, disclosure documents, registrations, licenses, government spending, and international business registries across commercial, nonprofit, and public-sector organizations.
Can Apriori link records about the same organization across different sources?
Yes. That is the core of what we do. Apriori maintains a resolved organization graph that links records about the same entity across sources and jurisdictions. Where supported by the underlying public record, it also preserves business relationships and organizational hierarchy, with provenance to the originating government record.
What is AI-driven entity resolution?
It is the process of deciding which records refer to the same real-world organization or licensed professional. Models propose links across sources; deterministic rules and provenance checks make the final call - so resolution decisions are rule-governed, reviewable, and traceable to source.
How is data delivered?
Three modes: bulk delivery of full datasets, API access, and monitoring - change detection that alerts on new filings, status changes, and registration events. All modes carry provenance back to the government source.
Which countries does Apriori cover?
Apriori covers the United States across the federal, state, and local jurisdictional hierarchy, plus international business registries across dozens of countries and languages, including national-scale datasets processed end to end.
Who uses Apriori data?
Teams responsible for compliance, KYC/KYB, due diligence, and risk - and product teams building AI applications that need a reliable, citable data layer for financial services, legal, healthcare, and government workflows.
What makes the data AI-ready?
Records are linked, deduplicated, and reconciled into resolved entities. Supported business relationships and organizational hierarchy are preserved rather than flattened. The result is structured, citable data with source provenance - the form LLM and RAG systems need to produce deterministic answers instead of guesses.
How do I engage Apriori?
Four models: bulk licensing of existing datasets, custom acquisition of sources you need, monitoring subscriptions for change detection, and a dedicated data-operations pod working under MSA/SOW inside your organization.