Human-in-the-Loop Evaluation with NIMBUS Uno | AI Testing, Interpretability & GenAI Reliability скачать в хорошем качестве

Human-in-the-Loop Evaluation with NIMBUS Uno | AI Testing, Interpretability & GenAI Reliability

Human-in-the-Loop (HITL) evaluation is essential for validating the true reliability and trustworthiness of Generative AI systems. In this video, learn how Nimbus Uno integrates expert review, manual annotation, and interpretability analytics to ensure that automated scores from AI evaluation pipelines genuinely reflect human judgment. NIMBUS enables reviewers to manually validate a selected sample of prompts and responses, scoring accuracy, relevance, coherence, and contextual grounding on a 0–10 scale. This process creates a human benchmark that confirms whether the model’s automated metrics, such as accuracy, precision, or hallucination scores, are dependable. Every annotation is saved, visualized, and mapped, helping teams instantly identify weak areas, problematic document sections, and patterns of poor reasoning. Nimbus also applies topic modeling to cluster sampled prompts and responses, revealing categories where the model’s performance shifts. Using conformal analysis, the platform compares human-assigned scores with model-generated scores, detecting inconsistencies, bias, or overconfidence in evaluation patterns. Finally, the residual analysis module provides a clear visualization of the gaps between human and model scoring, pinpointing where the AI underperforms and guiding targeted fine-tuning. By combining automated evaluation, human-driven assessment, and deep interpretability, NIMBUS ensures AI systems are accurate, transparent, and aligned with human intelligence. Contact us today for a demo: https://www.solytics-partners.com/pro... #ModelEvaluation #RAGValidation #RetrievalQuality #PerformanceMetrics #LLMTesting #AIGovernance #ModelValidation #NimbusUno #SolyticsPartners