Side-by-side comparison of AI visibility scores, market position, and capabilities
NYSE-listed federal IT integrator delivering cloud, cybersecurity, and AI solutions exclusively to DoD and civilian agencies. ~$7.3B annual revenue and ~$23.8B contract backlog.
Science Applications International Corporation (SAIC) is a Fortune 500 defense and government IT company headquartered in Reston, Virginia, founded in 1969. SAIC provides technology integration, cybersecurity, software development, cloud adoption, and digital modernization services exclusively to U.S. federal government clients including the Department of Defense, military branches, intelligence community, and civilian agencies.\n\nIn fiscal year 2025, SAIC reported revenues of approximately $7.26 billion with a contract backlog of $23.8 billion. The company has more than 24,000 employees and holds a portfolio of large-scale prime contracts spanning enterprise IT, command-and-control systems, intelligence analysis, logistics technology, and mission engineering. SAIC emphasizes a customer-first delivery model combining proprietary platforms with off-the-shelf commercial technology to accelerate modernization timelines.\n\nSAIC has been expanding its AI, machine learning, and autonomous systems capabilities to align with DoD priorities around AI-enabled warfare and digital engineering. Its digital transformation portfolio supports customers transitioning legacy infrastructure to multi-cloud environments compliant with FedRAMP, IL4, and IL5 security standards. The company is traded on the NYSE under the ticker SAIC.
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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