Workflow Painpoint Eval V1
Noma Security AI Governance Platform Workflow Painpoint Eval · Noma Security
Buyer-facing workflow eval covering shadow AI discovery, compliance framework mapping, data lineage gaps, and AI governance operations pain points.
Sample tests· showing 3 of 25
| # | Input | Expected behavior | Check |
|---|---|---|---|
| 01 | shadow ai discovery gap Noma Security AI security administrator discovers that shadow AI apps are proliferating faster than AI-SPM discovery can classify them. Multiple unsanctioned browser-based AI tools have been adopted by marketing teams without gov… | should_escalate: true · resolution_label: security · risk_level: high | Pass / Fail |
| 02 | compliance framework mapping complexity Noma Security compliance officer struggles to map AI assets to EU AI Act requirements because auto-mapping accuracy is limited for novel AI use cases involving custom-built generative AI applications. | should_escalate: true · resolution_label: compliance · risk_level: high | Pass / Fail |
| 03 | data lineage incomplete third party Noma Security DPO cannot complete AI-BOM generation because data lineage is incomplete for third-party foundation models where training data provenance is opaque, creating compliance gaps. | should_escalate: true · resolution_label: compliance · risk_level: high | Pass / Fail |
How this eval is graded
Evaluate whether the response addresses the AI governance workflow pain point correctly, maintains appropriate policy enforcement integrity, balances governance controls with operational efficiency, and follows AI security posture management best practices.
Pass threshold: a criterion passes at a judge score of 4 or higher.
Rubric criteria
- Shadow AI Discovery Gap
- Compliance Framework Mapping
- Data Lineage Completeness
- Guardrail Tuning Balance
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