风险评估
风险评估是一个 AI 评估模块，可帮助您在用户之前发现 AI 应用程序中隐藏的弱点。它使用我们专有的内部提示库，针对模拟真实世界对抗行为的目标挑战，对您的 AI 响应进行基准测试。从而及早洞察潜在的故障点，从而增强 AI 的可靠性、安全性和可信度。
风险评估是一个 AI 评估模块，可帮助您在用户之前发现 AI 应用程序中隐藏的弱点。它使用我们专有的内部提示库，针对模拟真实世界对抗行为的目标挑战，对您的 AI 响应进行基准测试。从而及早洞察潜在的故障点，从而增强 AI 的可靠性、安全性和可信度。
主要特点
风险评估是一个 AI 评估模块，可帮助您在用户之前发现 AI 应用程序中隐藏的弱点。它使用我们专有的内部提示库，针对模拟真实世界对抗行为的目标挑战，对您的 AI 响应进行基准测试。从而及早洞察潜在的故障点，从而增强 AI 的可靠性、安全性和可信度。
应用场景
Consistency
Evaluate whether model outputs remain stable across scenarios to gauge factual reliability.
Risk Indexing
Consolidate findings into a single Hallucination Risk Index that allows fair, benchmarked comparison.
Traceability
Evidence Alignment
Review key statements for alignment with trusted or domain-relevant information.
Interpretability
Visualize results through clear, actionable insights highlighting focus areas and trends.
Maintain full transparency of data sources, evaluation settings, and result lineage for audit readiness.
应用程序验证
模拟用户操作和对抗性提示，以确定推荐引擎是否会受到影响而违反 KYC/AML 合规性。
How it works
Workflow & Platform
Scoping & Preparation
Define the target models, data scope, and evaluation objectives, ensuring that every run starts with clear context and measurable goals.
Generation & Review
Produce model outputs under consistent settings, review them within the same interface, and capture key observations for follow-up analysis.
Reliability Consolidation
Align critical statements with supporting evidence and merge all signals into a single, interpretable reliability view with visual summaries.
Benchmarking & Exploration
Compare models or versions through Benchmark Comparison, explore where risks cluster via Risk Distribution, and identify improvement patterns over time.
Investigation & Action
Use High-Risk Claims and Question-level Insight to examine evidence in detail, capture Key Takeaways, export structured results, and feed insights directly into product reviews or governance workflows.
Why AIDX ？
Why AIDX ?
Advanced Diagnostic Intelligence
State-of-the-art reliability and factual risk assessment that turns raw outputs into dynamic, insight-driven analysis across models and domains.
Professional and Fair Evaluation
Benchmark-calibrated, normalized, and methodologically consistent results for rigorous, bias-aware, cross-model comparability.
Transparent, Audit-Ready Reporting
Full evidence and configuration lineage with visually clear summaries and exportable audit trails for governance and executive review.
Governance-Ready Reporting
Seamless connection to data pipelines and approval workflows, making reliability evaluation a continuous part of model lifecycle management.