Side-by-side comparison of AI visibility scores, market position, and capabilities
Lano is a global payroll consolidation and contractor management platform, connecting HR teams with local payroll providers in 150+ countries.
Lano was founded in 2018 in Berlin, Germany and raised over $35M to build a global payroll aggregation layer that solves a distinct challenge from full EOR platforms: helping companies that already have local legal entities in multiple countries consolidate payroll data, payments, and reporting across their existing network of local payroll providers. Rather than replacing those providers, Lano connects to them via integrations and API, presenting a single view of global payroll in one interface.\n\nThe platform also provides contractor management capabilities, allowing companies to onboard, manage, and pay independent contractors across 150+ countries with compliant contracts and consolidated payment runs. Lano's payment infrastructure handles multi-currency disbursements, FX conversion, and local payment methods, removing the friction of managing international contractor payments through traditional bank wire processes.\n\nLano targets mid-market and enterprise companies with established international operations and existing payroll vendor relationships, positioning itself as the coordination layer on top of their current setup rather than a replacement. This differentiated positioning puts Lano in a distinct competitive space from pure-play EOR vendors, competing instead with global payroll aggregators like CloudPay and Immedis while also serving the contractor management use case that overlaps with platforms like Deel and Remote.
a2z Radiology AI raised $20M in 2025 for its whole-body AI that simultaneously screens for 24+ conditions across CT scans — from incidental cancers to cardiovascular risk — in a single automated read.
a2z Radiology AI has developed a whole-body CT analysis platform that simultaneously screens for over 24 medical conditions across a single CT scan, including incidental cancers, coronary artery disease, aortic aneurysm, bone density loss, and organ abnormalities. The AI acts as a second reader that radiologists can use to catch incidental findings that fall outside the primary reason for a scan — a major source of missed diagnoses.
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