Safeguarding Enterprise Integrity: The Vital Role of Continuous Data Integrity Checks for LLM Apps

Explore the imperative of continuous data integrity checks fortifying enterprise data against errors, ensuring compliance, and fostering trust in AI-driven processes.

Comprehensive Performance Insight

  • ntuitive visualization of performance metrics versus meta-features, facilitating in-depth analysis and data authenticity.

  • Export clusters and plots for further analysis or integration with external tools.

Effective Outlier Detection

  • Probability distribution plots to highlight outliers in numerical and categorical meta-features, ensuring data quality.

  • Clear insights into data distribution and deviations from norms for detailed examination or integration into downstream processes.

Enhanced Token Management

  • Unknown token detection to aid in identifying model hallucinations by highlighting tokens not present in the training corpus.

  • Generate re-training datasets with discovered tokens, facilitating model refinement and improved performance.

Insightful Meta-Feature Analysis

  • Probability distributions of meta-features like toxicity, language, and sentiment provide valuable insights into data properties.

  • Export functionalities to extract outlier information or global insights for further investigation or reporting purposes.

See LLM Data Integrity Checks in Action

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