AI teams move fast, but security reviews often can’t keep up. That gap is exactly what Drel is built to close. Drel is an AI Security Review platform designed for security architects and AppSec teams that need more than a vague “report.” Instead, Drel helps teams run a pre-production security review in a structured way—so you can identify threats, attach supporting evidence, and reach a clearance decision you can actually export and sign.
Pre-production security review that produces a real clearance
With Drel, the goal isn’t to generate another document that teams debate after the fact. It’s to produce a defensible security clearance decision before your AI system goes live. Drel structures the work so the threats, evidence grading, required controls, and the sign-off chain are captured in one sitting—ready for an AI committee and practical for audit needs.
Purpose-built for AI, RAG, and agentic trust boundaries
Traditional threat modeling tools weren’t designed for the realities of LLM-based systems—especially retrieval authorization, prompt injection paths, and agentic tool use. Drel is purpose-built for AI security review, not generic AppSec workflows. That focus matters because many AI failures aren’t “model behavior” problems alone; they’re system and integration problems. Drel supports reviews that map to the frameworks and trust boundaries your stack already relies on, including internal RAG patterns and agentic workflows.
Clear outcomes: proceed, conditional, pilot, hold, or decline
A major strength of Drel is that it turns assessment into an action-oriented decision. Rather than leaving teams with recommendations that are hard to enforce, Drel supports clearance outcomes such as proceed, conditional, restricted pilot, hold, or decline. Each outcome is backed by graded evidence—explicit, inferred, assumed, unknown, missing, or verified—so stakeholders can see exactly why a decision was reached.
Evidence grading, production blockers, and an audit-ready sign-off chain
Drel helps teams avoid the common failure mode where security flags issues but can’t clearly define what must change before go-live. The platform produces named production blockers tied to required controls, owners, and deadlines. It also supports re-assessment triggers when systems change, which is critical for AI systems that evolve. Finally, Drel builds a multi-stakeholder sign-off chain across roles like CISO, AI Governance, and DPO, creating a versioned, timestamped record that an audit can rely on.
If you’re trying to ship AI, RAG, or agentic systems with less friction and more accountability, Drel offers a structured clearance approach that security teams can stand behind and product teams can plan around.
Bottom line: Drel helps you run AI security reviews before AI ships, with decisions and evidence your stakeholders can actually use.