Visualize application topology and attack paths to data stores.
Detect abnormal application communication patterns and respond by isolating suspicious software.
Allow only verified software and hosts to communicate. Apply 1-click segmentation with zero network changes.
Visualize application topology and attack paths to prioritize protection based on risk of application compromise, shrinking time to value.
Maximize coverage with the smallest policy set, automatically generated to drive IT efficiency.
Apply application identity based policies with one click, for gap-free coverage.
Apply adaptive and simplified policies to allow only verified workloads to communicate over approved pathways. Never trust, always verify.
Identify data stores and map communication pathways to understand your security risk. Prioritize protection based on risk of compromise.
Enable DevOps and SREs to build and deploy software with more security and with fewer disruptions to the SDLC. Machine-learned policy creation and enforcement allows auto-scaling in even the most elastic cloud environment.
"Edgewise sees its product as being more effective than complex microsegmentation, and even easier to use than relatively simpler next-gen firewalls."
"A new cybersecurity startup from the Boston area is continuing the trend of using machine learning technologies to both fortify and reduce complexity in businesses’ cyber defenses."
"New kid says it can do data center firewalls better. Upstart exits stealth this week with 'reinvented' protections."
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