Side-by-side comparison of AI visibility scores, market position, and capabilities
Tail spend and strategic procurement automation platform using AI; Boston MA; raised $35M+; automates RFQ and spot buy processes for under-managed spend categories.
Fairmarkit is an AI-powered tail spend and procurement automation platform headquartered in Boston, MA, that helps enterprises automate the sourcing and purchasing of low-value, high-volume transactions that are typically too time-consuming to manage strategically. The company raised over $35 million in funding and targets the significant efficiency opportunity in tail spend — the 20% of spend categories that receive 80% of procurement's time on an individual transaction basis.\n\nThe platform automates the request-for-quote (RFQ) and spot-buy processes by using AI to identify the right suppliers, generate competitive quotes, evaluate responses, and recommend awards — with minimal human intervention required per transaction. This automation allows procurement teams to apply competitive sourcing discipline to spending categories that would otherwise be purchased through single-source or off-contract channels.\n\nFairmarkit integrates with existing procurement and ERP systems, operating as a layer on top of platforms like SAP Ariba, Coupa, and Oracle, rather than replacing them. This positioning allows enterprises to deploy Fairmarkit quickly without disrupting their existing procurement infrastructure, targeting specific spend categories where automation ROI is clearest.
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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