Ai Trust & Performance Evaluation Platform (ai-tpep)

• Author(s):

  Niranchana V | Harikrishnan R | Sarveshwaran M | Suriyabharathi J

• Keywords:

  AI Evaluation Framework, Trustworthy AI, Machine Learning Assessment, Fairness Metrics, Robustness Testing, Explainability, Adversarial Attacks, Model Governance, Evidence Packaging, CI/CD Integration.

• Abstract:

  AI-TPEP (AI Trust & Performance Evaluation Platform) Is A Modular And Reproducible Framework For Comprehensive Evaluation Of Machine Learning Systems Across Key Trust Dimensions, Including Predictive Performance, Calibration, Fairness, Robustness, Explainability, Safety, And Privacy. The Platform Ingests Model Artifacts Or API Endpoints And Conducts Deterministic Benchmark And Stress Testing—such As Adversarial Attacks, Distribution Shifts, And Subgroup Analyses—within A Sandboxed Execution Environment That Captures Detailed Telemetry. Standardized Metrics Are Computed Using Explicitly Defined Normalization Transforms And Aggregated Into Configurable Subscores And A Composite AI Trust Score. AI-TPEP Also Generates Signed Evidence Packages Containing Raw Inputs And Outputs, Explanation Artifacts, Manifests, And Provenance Records To Support Independent Auditing. This Paper Presents The System Architecture, Formal Metric Formulations, And Parameterized Test Catalogs For NLP/LLM And Vision Models, Alongside A Reference Implementation With CI/CD Integration. Experimental Results Demonstrate Practical Trade-offs Among Trust Dimensions, And Deployment Guidance Is Provided To Help Organizations Make Transparent, Defensible, And Data-driven Model Governance Decisions.

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Other Details

• Paper id:

  IJSARTV12I5105509

• Published in:

  Volume: 12 Issue: 5 May 2026

• Publication Date:

  2026-05-26

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