BenchDX
Bench Diagnose
AIDX LLM Safety Evaluation
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​AIDX provides a dedicated capability for LLM safety assessment. It focuses solely on safety—structured through a four-tier taxonomy with hundreds of categories that capture nuanced risk behaviors. Each category defines measurable criteria and standardized test patterns, enabling granular, reproducible, and evidence-based safety evaluation across diverse use cases.
Why it matters
Ensuring safe, compliant, and trustworthy AI before real-world deployment.
By providing measurable, auditable safety evidence, AIDX helps teams deploy LLMs confidently reducing uncertainty, protecting brand integrity, and meeting governance standards.
Early Risk Detection
Identify potential safety or ethical issues before real-world failures occur.
Compliance Documentation
Generate audit-ready reports aligned with regulatory requirements.
Lifecycle Risk Management
Cost & Uncertainty Reduction
Generate audit-ready reports aligned with regulatory requirements.
Trust & Transparency
Strengthen confidence among customers, partners, and regulators through open evaluation.
Maintain continuous observability and control across the entire AI lifecycle.
Core Capabilities
Category-based Safety Evaluation
Assess safety across hundreds of finely defined categories. Each evaluation run can target specific category sets, generating category-level results and comparative analytics.
Granular Result Visualization
Display performance by category, showing scores, distributions, and representative outputs for each selected dimension.
Automated Evaluation Management
Manage and monitor all evaluation tasks in one place. Track progress in real time, from creation to completion, with minute-level turnaround.
High-efficiency Execution
Parallelized evaluation pipelines ensure fast, stable, and scalable testing—delivering results within minutes, setting the industry benchmark for speed and reliability.
How it works
From risk definition to actionable evidence
Scope
Map the business use case to AIDX’s multi-level safety taxonomy and define measurable thresholds.
Generate & curate
Construct targeted evaluation datasets covering both standard and adversarial scenarios.
Execute
Run structured assessments across selected models or model versions under controlled conditions.
Evaluate
Quantify performance using industry-recognized safety metrics to ensure objective and reproducible comparison
Interpret
Synthesize results into interpretable summaries highlighting key strengths and potential risks.
Recommend
Provide clear, evidence-based improvement guidance for model alignment, prompt design, or policy optimization.
Key features of the capability
1
Standardized Benchmarking
Employs consistent, industry-accepted metrics for fair cross-model evaluation.
2
Interpretable Methodology
Provides transparent scoring logic and clearly defined evaluation criteria.
3
Traceable Evidence Base
Every result is backed by categorized test sets and documented behavioral analysis.
4
Policy Alignment
Evaluation thresholds and taxonomies are configurable to match organizational or regulatory frameworks.
5
Extensible Framework
Supports continuous evolution through the addition of domain-specific safety categories while maintaining comparability and methodological integrity.
Why AIDX ?
Methodology first
research-grounded scoring and rationales—not just dashboards.
Governance ready
artifacts structured for internal review boards and audits.
Lifecycle fit
supports pre-launch certification and post-launch regression monitoring
Composable
integrates with robustness/RAG checks; deployable as report, API, or embedded controls.