Permit.io vs a2z Radiology AI

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

Permit.io

EmergingDeveloper Tools

Authorization as a Service

Permit.io provides authorization as a service with a policy editor, audit logs, and SDKs that decouple permissions from application code for any stack.

About

Permit.io is an authorization platform founded in 2021 that provides developers with a complete solution for implementing fine-grained access control in their applications. The platform offers a cloud-hosted policy decision point, a visual policy editor for defining roles and permissions, real-time audit logging, and multi-framework SDK libraries for Python, Node.js, Java, and other languages. Permit.io is built on top of open-source policy engines including OPA (Open Policy Agent) and Casbin, providing an enterprise-ready hosted service layer on top of proven open-source foundations. The company raised $7M and targets engineering teams that need to implement permission models ranging from simple RBAC to complex ABAC and relationship-based access control without building policy infrastructure from scratch. Permit.io's developer-first approach includes GitOps integration for managing policies as code and a sandbox environment for testing permission changes before production deployment. The platform serves SaaS companies, enterprise applications, and multi-tenant platforms that require auditable, testable access control that can evolve as product requirements change.

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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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