Earthly vs a2z Radiology AI

Side-by-side comparison of AI visibility scores, market position, and capabilities

Earthly

EmergingDeveloper Tools

Build Automation

Open-source build automation tool that runs builds in containers for reproducibility across local and CI environments.

About

Earthly is an open-source build automation framework that runs build steps inside containers, ensuring that builds produce identical results on developer laptops and in CI systems regardless of the underlying environment. Earthly's Earthfile syntax combines familiar concepts from Dockerfile and Makefile, making it approachable to teams already using containers without requiring deep build system expertise. The containerized execution model eliminates the classic "works on my machine" problem by ensuring every dependency is pinned and every environment is identical. Earthly supports parallel execution of independent build targets and efficient layer caching to minimize build time. The company offers Earthly Satellites, a managed remote build service, for teams that need consistent build performance in CI. Founded in 2020 with backing from Uncork Capital and 468 Capital, Earthly has gained adoption among developer teams frustrated with the complexity of existing CI systems and the inconsistency of language-specific build tools. It competes with Bazel, Make, and language-specific build systems in the reproducible build market.

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a2z Radiology AI

EmergingEnterprise AI

Medical Imaging AI

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.

About

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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