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Streamline Your MLOps Pipeline

MLOps is critical for successful machine learning deployments, but managing the ML lifecycle can be challenging. Aporia's ML observability platform can help you streamline your MLOps pipeline by providing real-time model monitoring, model explainability, and seamless integration with your existing MLOps tools and workflows. With Aporia, you can accelerate the delivery of your ML applications and ensure the reliability, scalability, and repeatability of your ML models.

Ensure your machine learning models in production are performing at their best, improve your ML workflow.

Thousands of data science & ML teams use us to achieve their AI goals

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See Your Models Shine in Production

More than just a Monitoring platform

Monitor, Visualize, & Improve Your Models in Production

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Centralized, real-time view of model health & performance

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Live Alerts

Detect drifts, bias and data integrity issues

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Get to the root cause and improve models with production data

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Know the why behind your models predictions

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Start Monitoring Your Models in Minutes

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Centralize Your Models in Production, Simplify MLOps

Scale with Confidence

Aporia’s MLOps platform streamlines your ML workflow to maximize efficiency.

Collaborate with Ease

Simplify your MLOps workflow with Aporia. Visualize ML metrics, compare models with ease.

Advanced ML Monitoring

Track your ML models with Aporia's Quick & Easy Setup. Detect drifts early and optimize your MLOps workflow.

Model Insights

Detect drift & model degradation, gain valuable insights, and ensure ML ROI.

Support Any Use Case

You know your models and use case best. Customize monitoring based on your specific requirements to ensure your models stay on track and perform at their peak.

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Customer LTV

Monitor behavior patterns, segment customers, and take action accordingly to ensure that the customers you invest in generate revenue and profits.

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Dynamic Pricing

Boost sales and respond quickly to changes in market demand, inventory levels, and competitor pricing to ensure you’re not overpricing potential customers.

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Recommender Systems

Scale recommender systems in production. Drive more revenue, increase conversions and engagement, and enhance trust in your models’ recommendations.

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Lead Scoring

Ensure your Lead Scoring Model is providing its intended value so that you can nurture the leads that will actually lead your business to success.

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Churn Prediction

Win back customers by increasing retention rate and accurately predicting customer churn rate with

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Credit Risk

Ensure that your Credit Risk Model performs as intended so that you can rest easy knowing that your loans are compliant, fair, and repaid (with interest, of course).

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Fraud Detection

Ensure your Fraud Detection Model works as intended so that you keep the customers that generate your revenue and profit -- and ditch the bad eggs.

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Demand Forecasting

Improve your business's ability to capitalize on ever-changing demand and ensure that you aren't missing out on sales nor losing money on wasted inventory

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Ensure your Language Models are performing as intended with real-time model monitoring, live drift alerts, and explainability.


Aporia naturally fits into your workflow

Amazon S3 Amazon S3
Glue Glue
Snowflake Snowflake
BigQuery BigQuery
Databricks Databricks
Azure Blob Storage Azure Blob Storage
Redshift Redshift
PostgreSQL PostgreSQL
Athena Athena
Delta Lake Delta Lake
Spark Spark
Ray Ray
New Relic New Relic
Grafana Grafana
Prometheus Prometheus
DataDog DataDog
Azure ML Azure ML
Vertex AI Vertex AI
AWS Sagemaker AWS Sagemaker
TensorFlow TensorFlow
LightGBM LightGBM
Hugging Face Hugging Face
Scikit Learn Scikit Learn
PyTorch PyTorch
dmlc XGBoost dmlc XGBoost
CatBoost CatBoost
Spark MLib Spark MLib
Slack Slack
Microsoft Teams Microsoft Teams
Jira Jira
PagerDuty PagerDuty
Opsgenie Opsgenie
Email Email
Webhook Webhook
MLFlow MLFlow
Kubeflow Kubeflow
KServe KServe
Feast Feast
Weights & Biases Weights & Biases
ClearML ClearML

Data Sources

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Amazon S3

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Azure Blob Storage

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Delta Lake

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DevOps Infrastructure Monitoring

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New Relic

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Cloud Providers

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Azure ML

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Vertex AI

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AWS Sagemaker

ML Frameworks

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Hugging Face

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Scikit Learn

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dmlc XGBoost

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Spark MLib


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Microsoft Teams

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MLOps - Complementary MLOps Tools

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Weights & Biases

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“In a space that is developing fast and offerings multiple competing solutions, Aporia’s platform is full of great features and they consistently adopt sensible, intuitive approaches to managing the variety of models, datasets and deployment workflows that characterize most ML projects. They actively seek feedback and are quick to implement solutions to address pain points and meet needs as they arise.”

Felix D.

Principal, MLOps & Data Engineering

“As a company with AI at its core, we take our models in production seriously. Aporia allows us to gain full visibility into our models' performance and take full control of it."

Orr Shilon

ML Engineering Team Lead

“ML models are sensitive when it comes to application production data. This unique quality of AI necessitates a dedicated monitoring system to ensure their reliability. I anticipate that similar to application production workloads, monitoring ML models will – and should – become an industry standard.”

Aviram Cohen


“With Aporia's customizable ML monitoring, data science teams can easily build ML monitoring that fits their unique models and use cases. This is key to ensuring models are benefiting their organizations as intended. This truly is the next generation of MLOps observability.”

Guy Fighel

General Manager AIOps

“ML predictions are becoming more and more critical in the business flow. While training and benchmarking are fairly standardized, real-time production monitoring is still a visibility black hole. Monitoring ML models is as essential as monitoring your server’s response time. Aporia tackles this challenge head on.”

Daniel Sirota

Co-Founder | VP R&D

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Start using Aporia now