AI Dashboard

Overview

Monitor, analyze, and optimize AI model performance in real time.
The AI Dashboard centralizes model metrics, training progress, usage analytics, and performance insights in a responsive, intuitive interface - helping data scientists and ML engineers track AI efficiency, identify issues, and make data-driven improvements quickly.

Key Features

Real-Time Model Monitoring & Metrics

‍Track model KPIs such as accuracy, precision, recall, F1-score, latency, and data drift indicators. Gain immediate insights into model performance and potential bottlenecks with interactive dashboards.

Version Comparison & Error Analysis

‍Compare different model versions, evaluate confusion matrices, and monitor error distributions to identify areas for improvement and optimize AI workflows.

Training Progress & Hyperparameter Tracking

‍Visualize ongoing training jobs, epochs, loss curves, and completion rates. Access detailed hyperparameter settings to understand model behavior during training.

Usage Analytics & Resource Monitoring

Monitor API calls, model load, and resource utilization. Analyze high-demand models, detect bottlenecks, and ensure infrastructure efficiency.

Alerts & Notifications

‍Receive timely updates about anomalies, degraded model performance, or significant changes in metrics to enable proactive decision-making.

Use Cases

• AI model performance monitoring for ML engineering teams
• Tracking training & inference efficiency across multiple models
• Resource utilization and anomaly detection dashboards
• Centralized performance insights for data science operations

Start Building Your Own AI Dashboard

Use this AI Dashboard template as a foundation to create a fully custom AI monitoring platform. Connect live model metrics, visualize training progress, monitor usage analytics, and set alerts tailored to your AI workflows with UI Bakery’s low-code tools.