Why customers chooseSAFE vs. Zscaler (Avalor)
Why SAFE Wins Vs Zscaler
SAFE is recognized by Gartner and IDC as the leading autonomous CTEM platform, combining market-leading risk quantification, business-aligned prioritization, and fully configurable Agentic AI to outperform point solutions focused on tactical vulnerability triage.
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Better Risk-Based Prioritization As the market leader in risk quantification, SAFE incorporates deep business context for more accurate prioritization decisions. Zscaler has no such capabilities for exposure management, with prioritization less defensible - reliant on manual tuning and ad-hoc configurations. |
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Compensatory Controls SAFE incorporates the mitigating effects of compensating controls to ensure that valuable remediation effort is focused on the highest exposure findings. Zscaler lacks meaningful incorporation of controls, which forces teams to spend excessive time addressing vulnerabilities that have a low probability of exploitation. |
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Autonomous, Agentic AI SAFE is a 100% autonomous CTEM platform with fully configurable Agentic AI. Zscaler's automation workflow capabilities are rudimentary, focused heavily on ticket configuration and management. |
SAFE vs. Zscaler Overview
SAFE
SAFE is redefining cyber risk management with Agentic AI. We empower CISOs, cybersecurity, and TPRM leaders to continuously quantify, prioritize, and mitigate cyber risks across their entire attack surface - enabling digital growth and organizational resilience.
SAFE is the category leader in Cyber Risk Quantification (CRQ) and the first company to deliver 100% autonomous Third-Party Risk Management (TPRM) and Continuous Threat Exposure Management (CTEM).
Trusted by industry leaders including Google, Fidelity, T-Mobile, Chevron, and IHG, SAFE has achieved triple-digit revenue growth for three consecutive years and raised over $170 million to date.
Zscaler
Avalor (acquired by Zscaler) offers a data integration platform focused on building a centralized cyber asset data graph. The platform aggregates asset and vulnerability telemetry across an ecosystem of 3rd party tools and data sources, helping organizations map asset dependencies.
However, Zscaler's platform struggles when encountering messy or incomplete corporate asset data, as it has limited intelligence around normalization, deduplication and enrichment.
Furthermore, it is structurally isolated from broader business risk vectors, failing to incorporate financial risk quantification or consider the operational effectiveness of compensating controls.
Trusted By 10% of Fortune 500
