How OpenNash Hiring Intelligence collects official Forbes Global 2000 jobs, tracks weekly change, preserves descriptions, discloses gaps, and controls SEO publication.
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The data contract contains 2,001 locked Forbes Global 2000 roster records covering 2,000 unique companies. One duplicate roster alias is canonicalized and counted once. Companies outside that universe are not added to improve traffic or inventory totals.
Collectors use public employer career pages and official public hiring interfaces. The system does not bypass authentication, access controls, or source restrictions.
Collections reconcile declared totals, pagination, stable role identities, canonical source links, and repeated complete generations. A source that fails twice rotates out until reviewed evidence changes.
Titles, descriptions, requirements, locations, work arrangements, employment types, seniority, compensation, and dates are retained only when the source supports them. Unsupported fields stay blank.
The operating target is a canonical weekly anchor for each supported company. Anchors track new, removed, and changed roles. Trend claims wait for comparable observations under the same source contract; source breaks and missed refreshes are disclosed rather than treated as hiring changes.
A company earns its own page only by passing the freshness, searchability, description-coverage and gap-disclosure checks. Companies that do not pass are not given a thin page: they stay in the interactive explorer, where the underlying evidence is still visible, until the evidence supports publication.
A public OpenNash Applied AI project that tracks observable official job postings and hiring signals for 2,000 unique companies across 2,001 locked Forbes Global 2000 roster records, including one canonicalized duplicate alias.
No. Each page states its coverage tier, freshness, description coverage, and known missing sources. Only strict release-verified inventories are presented as enterprise-complete.
The operating target is weekly collection of observable official openings and important-role descriptions, with lower-value descriptions rotating monthly. Actual evidence dates and coverage disclosures on each company page govern; a failed source refresh is never presented as current.
They are published only when an official governed field or job description states them. Missing evidence stays unknown and is never inferred as on-site, unpaid, or requirement-free.
OpenNash builds custom software and AI agents for customer support, back-office, and operational work inside existing systems, with security, auditability, and human review where it matters.
Product-covered means a useful, transparent public inventory or source record exists. Current-count observed, searchable inventory, description-usable, and strict enterprise-complete are independently measured. Useful partial coverage is never presented as zero or as complete.
Methodology last generated 2026-08-22.