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ML Observability

The most advanced ML observability solution on the market.

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AI today

Imagine your dream observability system for production ML. Aporia has it all and more.

Explainability

Know the why

Understand your AI’s reasoning and communicate model predictions to business stakeholders.

  • Discover which features impact your predictions the most and why.
  • Ensure that the model’s results and outputs are trusted.
  • Prevent issues like bias and drift in the future.
  • Easily communicate model results to key stakeholders.
  • Using XAI, you can also simulate “What If” scenarios.
  • Use our Data Point Explainer to debug your data at a specific point, and then re-explain in one click.

Visibility

Real-time view of model health

Create customized dashboards for each one of your production models.

  • Get a detailed dashboard for every live model minutes after integration.
  • Get a live, unified view of all your models in one place.
  • Track model activity, inference trends, data behavior, actual model performance (F1, Precision, RMSE, etc.) and more.
  • Create multi-segment visualizations.
  • Explore sub-performing patterns of tabular, NLP, LLM and CV models.

Live alerts

Detect drifts, bias and data integrity issues

Real-time model monitoring: Detect all types of drifts and monitor billions of predictions with zero sampling.

  • Monitor drift, performance, and data quality across diverse model types, from LLMs to traditional ML.
  • Every single prediction is monitored
    Tailor ML monitoring to your unique challenges and use case.
  • Analyze and compare performance shifts across training, validation, and production datasets.
  • Leverage native A/B testing tools to easily identify and confirm any variations in the model’s performance.
  • Get instant notifications to your preferred communication channels.

Investigation

Get to the root cause

Troubleshoot ML models with ease, no need to export to external notebook.

  • Gain insights, discover patterns, and find the root cause of triggered alerts.
  • Save time investigating production data.
  • Effectively visualize embeddings in unstructured data through 2D/3D projections using UMAP.
  • Explore and investigate the performance of NLP, LLMs, and CV models with precision.

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for their ML models.

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The ML Observability Suite

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