S
Evaluation AuthorityAPAC · GCCv1.0 · Preview

Sovereign AI Evaluation Control Plane

From model sovereignty to evaluation sovereignty: proving AI is safe, useful, lawful, and culturally fit for deployment.

Sovereignty Score
74 / 100

Measures how much of the evaluation stack is locally governed.

Benchmark Dependency Risk
High

Share of deployment decisions relying on foreign benchmark assumptions.

Local Language Coverage
61%

Coverage across official languages, dialects, code-switching, and low-resource variants.

Regulator Alignment
82%

Mapped to local AI governance, data protection, financial, healthcare, and public-sector requirements.

Sector Deployment Readiness
Medium

Readiness across banking, healthcare, legal, education, and government services.

The Sovereignty Gap

Two competing evaluation paths

Hero analysis

Imported Benchmark Path

External authority
  • MMLU / HELM / generic safety evals
  • English-heavy assumptions
  • Western academic knowledge
  • Generic toxicity & safety definitions
  • Weak local regulatory mapping
  • Low cultural-context coverage
Final approval stamp
FBForeign Benchmark Authority
GAP

"Local infrastructure without local evaluation still imports foreign judgment."

Sovereignty delta

Sovereign Evaluation Path

Local authority
  • Domestic golden datasets
  • Region-calibrated judge models
  • Regulator-aligned rubrics
  • Local language and dialect testing
  • Sector-specific failure libraries
  • Deployment readiness by jurisdiction
Final approval stamp
LALocal Evaluation Authority
DCModel in local data center → approved by foreign benchmark.
DCModel in local data center → approved by local evaluation authority.
Visualization 01

Benchmark Assumption Map

Coverage analysis
Benchmark
Local law
Local language
Cultural context
Sector-risk
Regulator traceability
Public-sector admissibility
Domain failure realism
MMLUGapGapGapGapGapGapGap
HELMGapPartialGapGapPartialGapGap
Generic safety benchmarkGapPartialGapPartialGapGapPartial
Internal enterprise evalPartialPartialPartialFullPartialPartialFull
Sovereign evaluation stackFullFullFullFullFullFullFull
Insight · Global benchmarks are useful baselines. They are not final deployment authorities.
Visualization 04

AI Deployment Fitness Score

Global 88%Sovereign 63%
CapabilitySafetyLocal legal fitLocal language fitCultural fitSector fitAuditabilityHuman escalationInstitutional trust
Capability
95 / 80
Safety
90 / 78
Local legal fit
70 / 68
Local language fit
60 / 70
Cultural fit
50 / 60
Sector fit
65 / 65
Auditability
55 / 60
Human escalation
50 / 55
Institutional trust
60 / 58
Annotation · A model can be globally impressive but locally unsafe, unlawful, or institutionally unusable.
Regional intelligence

Jurisdiction readiness across APAC & GCC

Switch between Singapore, UAE, Saudi Arabia and India to inspect language, regulator, sector, and dataset requirements.

Visualization 02

Jurisdiction Readiness Panel

Local language requirements
  • · English
  • · Mandarin
  • · Malay
  • · Tamil
  • · Singlish / code-switching
Data protection / AI governance
  • · MAS FEAT principles
  • · PDPA
  • · IMDA Model AI Governance
  • · AI Verify
High-risk deployment sectors
  • · Financial services
  • · Legaltech
  • · Healthcare
  • · Public services
Cultural-context risk areas
  • · MAS-grade auditability
  • · PDPA consent
  • · Multilingual citizen service
  • · Explainability
Required golden datasets
  • · SG financial advice corpus
  • · Public-service Q&A
  • · Multilingual hawker / civic queries
Judge model calibration
  • · MAS-aligned conduct evaluator
  • · Singlish dialect evaluator
  • · Healthcare safety evaluator
Sovereignty maturity
78
/100
Regulator rubric: Mature
Score blends language coverage, regulator alignment, golden-dataset depth, judge calibration and sector readiness for Singapore.
Architecture

The five-layer sovereign evaluation stack

From domestic golden datasets to the deployment readiness gate — each layer must be governed locally.

Visualization 03

Sovereign Evaluation Stack

5 layers
L1
Domestic Golden Datasets
Local lawLocal languageLocal cultural contextLocal domain scenariosPublic-sector cases
L2
Region-Calibrated Judge Models
Local reasoning evaluatorLocal harm evaluatorDialect-aware evaluatorSector-risk evaluatorRegulator-aligned evaluator
L3
Regulator-Aligned Rubrics
Data protectionFinancial conductHealthcare safetyPublic-sector accountabilityExplainability & auditability
L4
Sector Failure Library
Banking failuresHealthcare escalation failuresLegal citation failuresGovernment eligibility failuresEducation bias failures
L5
Deployment Readiness Gate
ApproveConditionally approveEscalate to human reviewBlock deploymentRequire local retraining
Visualization 05

Failure Case Simulator

Interactive
Imported benchmark verdict
Pass — coherent and helpful answer.
Sovereign evaluation verdict
Fail — violates banking conduct expectations in Singapore and requires escalation.
Risk explanation
AI assistant gives investment suitability advice without adequate risk disclosure.
Required mitigation
  • Add suitability guardrail
  • Advice boundary
  • Audit trail
  • Human advisor handoff
Human escalation trigger
Trigger: high-impact financial advice without disclosure → route to licensed human advisor.
Evidence trace
› Rubric: Singapore Banking v2.3 · clause 4.1.2
› Judge model: Singapore-BAN-Eval-04
› Golden dataset: Singapore-Banking-Conduct-2025Q3
Visualization 06

Benchmark Power Index

Dependency levels
Foreign academic benchmarks
92%
Vendor-provided evals
78%
Internal company evals
55%
Regulator-linked evals
34%
Domestic sovereign evals
18%
Strategic note · The future AI power question is not only who builds the model. It is who defines the test.
Executive Layer

Recommendation Engine

6 directives
01
Build domestic golden datasets for high-risk sectors
02
Establish national judge-model calibration standards
03
Require local-language and dialect evals before deployment
04
Map evaluations to regulator-specific obligations
05
Create public-private evaluation sandboxes
06
Certify AI systems by deployment fitness, not just global benchmark performance
Outputs a board-grade PDF summary across 7 dimensions.
Closing directive

Sovereign AI without sovereign evaluation is branding, not sovereignty.