Overview

FlareAI is a technical solution that enables data providers to supply training samples while allowing AI users to access higher-quality training data. Below are the key evaluation dimensions and methods we apply to data:

Evaluation Dimensions:

• Accuracy: Ensures data correctness and proper labeling.

• Completeness: Checks for full data coverage with no missing values.

• Consistency: Verifies uniformity across different sources and times.

• Relevance: Assesses data suitability for specific tasks.

• Stability: Ensures stable data distribution over time.

• Diversity: Evaluates coverage of all relevant scenarios.

Evaluation Methods:

• Statistical Analysis: Uses statistical tools to assess data quality.

• Data Visualization: Employs visual methods to detect patterns and anomalies.

• Data Quality Scoring: Combines dimensions into an overall quality score.

• Automated Tools: Utilizes technology for automated data quality checks.

This concise approach ensures that FlareAI consistently delivers high-quality training data.