Aporia is an advanced Machine Learning (ML) observability platform that offers a centralized, real-time view of model health and performance. It is designed to monitor ML models in one comprehensive dashboard, ensuring optimal performance.

Key Features

• ML Observability Dashboards: Provides a centralized, real-time view of model health and performance.
• Explainability: Offers insights into the logic behind your models’ predictions.
• Root Cause Analysis: Helps to identify patterns, new opportunities, visualize unstructured data, and pinpoint the root cause.
• ML Monitoring: Detects drifts, bias, and data integrity issues.
• Live Alerts: Sends live alerts to Slack/MS Teams on any drift, bias, or data integrity issues.
• Big-Data Support: Connects directly to your data lake – Redshift, S3, Athena, Databricks, Snowflake, and BigQuery – without duplicating your data.
• Customization: Allows tailoring dashboards to track inference trends, data behavior, and performance.

Use Cases

The platform can be used in various ML use cases such as:

• Recommender Systems
• Customer Lifetime Value (LTV)
• Dynamic Pricing
• Demand Forecasting
• Churn Prediction
• Fraud Detection
• Credit Risk
• Natural Language Processing (NLP)
• General AI Use cases like Chatbots, Virtual assistant, Writing companion, Employee empowerment, Responsible AI, ML Integrity, Bais & Fairness, Compliance & Security