Validate model performance

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

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Models break in prod, we know that most of the time it's not your fault

In production environments, unpredictability is a given. Models that were once reliable in staging can deviate due to external influences like concept drift or changes to data pipelines. Consistent model performance is vital, and with a monitoring solution, you can quickly detect and fix drifts, ensuring prediction reliability and model integrity.

Monitoring models has never been easier

Simple setup with segment-level monitoring ready in minutes

  • Monitor drift, performance, and data quality across diverse model types, from LLMs to traditional ML.
  • Gain peace of mind with automated monitoring of your models, data schema, and features.
  • Focus on building models, let Aporia’s model monitoring do the leg work for you.
  • Handling billions of predictions? Rest assured that every single prediction is monitored, leaving no room for errors or sampling.

Full customization: Your model, your rules.

Tailor ML monitoring to your unique challenges and use case.

  • Monitor metrics tailored to your needs, leveraging an SQL-like query for deriving new metrics.
  • Benefit from continuous auto-thresholding, making the monitoring system highly practical and efficient.
  • Set static thresholds or dynamic ones that are influenced by patterns in the incoming data.
  • Ensure your monitoring approach remains dynamic, adapting to your model’s evolving needs.

Examine different environments & versions

Dive deep into the nuances of your models and compare behaviours across datasets & versions

  • 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.
  • Monitor your model’s progression and behavior across various versions and updates.

Alerts, on your terms

Get instant notifications to your preferred communication channels.

  • Choose from a range of alerting options, from emails and MS Teams to Slack notifications.
  • Define urgency thresholds to avoid alert fatigue.
  • When drift is detected, an investigation case is instantly initiated. The goal is to solve issues, not just point to them.
Build vs. Buy - ML Observability

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Loved By

See why Data Scientists, ML Engineers and Business Stakeholders love Aporia.

Aporia is a leader in AI & Machine Learning Operationalization on G2
Orr Shilon

ML Engineering Team Lead

“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

Aviram Cohen

VP R&D

“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

VP R&D

Guy Fighel

General Manager AIOps

“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

Daniel Sirota

Co-Founder | VP R&D

“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

Lukas Olson

Data Scientist

“We develop and deploy models that impact students' lives across the country, so it's crucial that we have good insight into model quality while ensuring data privacy. Aporia made it easy for us to monitor our models in production and conduct root cause analysis when we detect anomalous data."

Lukas Olson

Data Scientist

Carlos Leyson

Data Scientist

“As an early stage startup, starting to launch ML models in the fintech sector, monitoring the predictions and changes in our data is critical, and Aporia has made it easy by providing the right integrations and is easy to use."

Carlos Leyson

Data Scientist