A leading U.S.-based financial services company has reduced application risk by 98% after integrating CloudDefense.AI into its application security workflow. The company’s identity remains confidential under a strict NDA.
The organization operates in an environment where release velocity and security expectations are both high. With frequent deployments, expanding codebases, and a constant flow of third-party dependencies, the company needed a way to make application security feel less like a recurring fire drill-and more like a steady, repeatable part of shipping software.
Most teams aren’t struggling to find issues-they’re struggling to decide what matters and move quickly”
— Abhi Arora, COO at CloudDefense.AI
Before adopting CloudDefense.AI, the security and engineering teams faced a common issue in modern AppSec programs: findings arrived in batches, prioritization was difficult, and developers often needed extra context before acting. Questions like “Is this actually exploitable?” “Is it reachable in production?” and “Is this truly urgent?” repeatedly slowed down decision-making. Over time, that uncertainty created friction and stretched remediation cycles.
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By integrating CloudDefense.AI, the company shifted toward a workflow designed to reduce ambiguity and keep remediation moving. The organization established a baseline both security and engineering teams could trust, focused attention on issues that materially affected exposure, and built a consistent loop for routing fixes, validating closure, and tracking progress.
The result was a measurable drop in application risk-98% – and a process that could be maintained without relying on constant triage meetings or manual reporting.
The financial services company continues to strengthen its application security posture while maintaining delivery cadence, using the same risk-based workflow to keep exposure from creeping back over time.
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