> For the complete documentation index, see [llms.txt](https://docs.aquilax.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.aquilax.ai/blog/ai/ai-driven-vulnerability-triage.md).

# AI-Driven Vulnerability Triage

AI-Driven Vulnerability Triage: The AquilaX Approach

<figure><img src="https://53914109-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FjAmSnvnfbHl4EDK56iDo%2Fuploads%2Fgit-blob-856c59e8c68869ea10a47ff624a15d1f7b8826d6%2Fachieved-accuracy.png?alt=media" alt=""><figcaption><p>AI-Driven Accuracy in Security Reviews</p></figcaption></figure>

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Traditional Static Application Security Testing (SAST) tools generate excessive noise, overwhelming security teams with false positives. The AquilaX AI-powered Findings Review Model transforms this process by automating vulnerability classification with high accuracy and efficiency. Using machine learning and real-world security insights, it significantly reduces false positives, streamlines triage, and enhances DevSecOps workflows. This cutting-edge AI solution ensures that security teams focus on critical threats, eliminating the manual burden of reviewing low-risk findings.

Download the white-paper here: <https://aquilax.ai/ai-driven-accuracy-in-security-reviews>