Drel vs. AI Security Posture Management tools
AI-SPM tools scan your runtime environment — cloud configurations, deployed models, API exposure. Drel produces the design-time security review record your AI Committee signs before any of that is deployed. The timing is different, the artifact is different, and the buyer is different.
AI Security Posture Management is a real category solving a real problem: once AI systems are running in production, someone needs to continuously monitor their configuration, detect drift, and surface misconfigurations before they become incidents. That is a runtime problem.
Drel solves a different problem at a different point in the lifecycle. The AI Committee's question is not “what is the current posture of our deployed systems?” It is “can this system reach production, and what is the defensible record that we reviewed it before it did?” That is a design-time governance problem.
AI-SPM tells you what your deployed systems look like right now. Drel tells you whether a system was cleared to deploy in the first place, and what the AI Committee signed off on. Both questions matter. They are answered at different times.
What AI-SPM tools do
- Scan cloud environments for AI-related misconfigurations — exposed model endpoints, overpermissioned service accounts, unencrypted model artifacts.
- Inventory deployed AI models and APIs across cloud accounts.
- Detect runtime drift: a model that was reviewed in one configuration is now running in another.
- Alert on new AI assets that were not reviewed before deployment.
- Integrate with CSPM and cloud-native security tooling.
The buyer is typically the cloud security or AppSec team. The artifact is a posture dashboard and alert stream. The timing is continuous.
What Drel does
- Produces a structured security model of an AI system from its architecture description — before it is deployed.
- Maps the system to a threat register, control plan, and evidence gap list.
- Generates a Risk Disposition memo: the AI Committee's decision, rationale, required controls, residual risk acceptance, re-assessment triggers, and sign-off log.
- Produces an audit-ready dossier that supports ISO 42001, EU AI Act Article 9, and OWASP Agentic Top 10 evidence requirements.
The buyer is the AI Governance team, Security Architecture, or the CISO's office. The artifact is a versioned clearance record. The timing is design-time, before production — and at each re-assessment trigger thereafter.
Side by side
| Capability | Drel | AI-SPM tool |
|---|---|---|
When it runs | Design-time, before production. Re-runs at each re-assessment trigger (model change, tool added, scope expansion). | Continuously, against deployed production environments. |
Primary input | Architecture description, system intake, threat model. | Cloud API access, deployed infrastructure scan. |
Primary output | Risk Disposition memo + audit-ready dossier. The AI Committee's signed decision record. | Posture dashboard, misconfiguration alerts, asset inventory. |
Primary buyer | AI Governance, Security Architecture, CISO office. | Cloud security team, AppSec, SOC. |
Requires production access | No. Drel does not ingest live telemetry or scan running environments. | Yes — requires cloud API credentials and runtime access. |
Framework mapping | ISO/IEC 42001, EU AI Act Art. 9, NIST AI RMF, OWASP Agentic Top 10, AIUC-1. | Typically CSPM frameworks (CIS, NIST 800-53). AI-specific frameworks vary by vendor. |
Governance artifact | Versioned clearance record with sign-off log. Defensible in audit. | Posture score and alert history. Not a governance decision record. |
Re-assessment triggers | Typed events (model change, tool added, autonomy increase, vendor change) encoded in the disposition. | Continuous drift detection against deployed configuration. |
Coexists with AI-SPM | Yes — Drel produces the pre-deployment record; AI-SPM monitors what was deployed. | — |
How the two fit together
The cleanest model we have seen: Drel produces the clearance record before deployment. The AI-SPM tool monitors the deployed system against the configuration that was cleared. When the AI-SPM tool detects drift — a new model version, an added API endpoint, a changed permission scope — that drift fires a re-assessment trigger in Drel, which produces an updated clearance record.
The two tools answer different questions for different stakeholders. The AI Committee reads the Drel disposition. The cloud security team reads the AI-SPM dashboard. The connection between them is the re-assessment trigger.
See the clearance record Drel produces
The Risk Disposition Drel generates for an enterprise AI system is the artifact your AI Committee signs before deployment. Read a sample, then decide whether your current pre-deployment governance process produces the same artifact.
A note on scope: Drel reviews assessed systems against documented architecture, configuration and intent. It does not ingest live telemetry from production environments. Dispositions reflect the assessed system at the time of review and the re-assessment triggers that govern when the disposition must be revisited.