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Machine Learning Driven Zero Trust Security

Zero Touch. Zero Trust.

Edgewise’s Zero Trust platform uses machine learning to maximize protection coverage, increase confidence in policies, and drive operational simplicity—while raising the cost and complexity for attackers. The machine learning system has three outcome-driven stages; the first reveals risk of exposure, the second builds optimal policies, and the third protects workloads while continuously assessing their trustworthiness.

Simple for defenders. Complex for attackers.

Faster time to value

Faster time to value for the business

Application owners, within hours, can understand the intended state of their environment and exposure risk. Edgewise automatically verifies the identities of workloads communicating by applying Zero Trust principles. Edgewise machine learning builds these secure identities by collecting and analyzing data from deep within the operating systems' kernel. Edgewise then maps the application topology based on communication pathways between workloads. Edgewise then measures exposure risk and analyzes attack paths to visualize overly exposed application pathways not required by the business.

Edgewise Policygraph Engine

More efficient DevOps

Edgewise builds Zero Trust policies that enforce least-privilege access to critical workloads and data. Because Zero Trust policies are based on secure identities of communicating workloads, they are more accurate and easily adapt to dynamic environments. Operations teams gain the broadest protection coverage with the fewest number of policies. The workload identity-based policies described in plain English enable application owners and DevOps to more effectively collaborate and protect business applications. One click is all it take to apply the Zero Trust policies and receive proof of correctness.

Gap-free security coverage

Gap-free security coverage

Edgewise’s Zero Trust platform ensures only verified software, users, containers, and hosts are allowed to communicate over approved network paths. The Zero Trust protection is enforced at the workload to ensure gap-free coverage when workloads move in hybrid environments. Edgewise machine learning continuously verifies the Zero Trust policies and alerts on deviations from intended state.


Edgewise Networks
Edgewise Protect

Zero Trust Protection For Application Workloads

Stop lateral movement of malicious software in untrusted cloud networks by allowing only verified applications to communicate over approved pathways.

Eliminates Network Attack Surface

Over 95% of network pathways are not required for normal business use. Eliminate unnecessary attack surface and protect the rest with zero trust policies.

Faster DevOps Security With Automated Policies

Edgewise automatically builds protection policies using machine learning, within 48 hours. Simply click Approve for zero trust protection.