EVIDENCE-BASED EVALUATION

OUR
METHODOLOGY

TrustVector evaluates AI systems through a rigorous, transparent,
and evidence-based framework.

Core Principles

Evidence-Based

Every score requires documented evidence from official sources, research papers, or verified testing results.

Transparent

All evaluation criteria, methodologies, and confidence levels are publicly documented and verifiable.

Community-Driven

Open-source evaluations reviewed by the community. Anyone can contribute improvements or new evaluations.

Continuously Updated

Evaluations are regularly updated as new versions, features, and research become available.

Five Trust Dimensions

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Dimension 1

Performance & Reliability

+

Measures task accuracy, output consistency, latency, uptime, and overall system reliability.

Key Criteria:
  • •Task completion accuracy (benchmarks like HumanEval, MMLU, SWE-bench)
  • •Output consistency and determinism
  • •Response latency (p50, p95)
  • •Uptime SLA and availability
  • •Context window and multimodal support
🛡️
Dimension 2

Security

+

Evaluates resistance to attacks, data protection, and security posture of the AI system.

Key Criteria:
  • •Jailbreak resistance and prompt injection defense
  • •Data leakage prevention
  • •Adversarial robustness
  • •Content filtering and safety guardrails
  • •Access controls and authentication
🔒
Dimension 3

Privacy & Compliance

+

Assesses data handling practices, regulatory compliance, and privacy protections.

Key Criteria:
  • •Data retention policies and user control
  • •GDPR, HIPAA, and SOC 2 compliance
  • •Data sovereignty and geographic controls
  • •Encryption at rest and in transit
  • •Training data usage policies
👁️
Dimension 4

Trust & Transparency

+

Evaluates documentation quality, model transparency, and organizational trustworthiness.

Key Criteria:
  • •Model documentation completeness
  • •Training data transparency
  • •Safety testing and bias evaluation disclosure
  • •Decision explainability
  • •Version management and changelogs
⚙️
Dimension 5

Operational Excellence

+

Measures ease of use, deployment flexibility, cost efficiency, and operational maturity.

Key Criteria:
  • •Deployment flexibility (API, self-hosted, cloud platforms)
  • •API reliability and rate limits
  • •Cost efficiency and pricing model
  • •Monitoring and observability tools
  • •Documentation and support quality

Scoring System

Score Ranges (0-100)

90-100
Exceptional
75-89
Strong
60-74
Adequate
40-59
Concerning
0-39
Poor

Confidence Levels

HIGHMultiple authoritative sources, recent data, official documentation
MEDIUMSome authoritative sources, community feedback, partial documentation
LOWLimited sources, older data, or inferred from general practices

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