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ML Observability for
Recommender Systems

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

See All your RecSys Models in One Place

Get a single pane of glass with everything you need to know about your models in production with Aporia.

Instantly build custom dashboards for your recommender systems, combining both business and data science metrics. Ensure your recommendations are making an impact by tracking your business KPIs such as Add To Cart rate, Purchase rate, or Swipe Right Rate.

Aporia Recommender Systems

Monitoring is More Than Recommended

Avoid bad recommendations that don’t get clicks. Use Aporia to stay on top of your production model’s performance by tracking key metrics such as nDCG@k, MRR@k, MAP@k, and easily running an array of behavioral tests specific to your recommender systems.

Aporia Recommender System

Understand Which Features Have the Greatest Impact

Providing curated recommendations in real-time with low latency can help you gain more value from customers anywhere in the world. Leverage Aporia’s Root Cause Investigation tool to know exactly when and where ML events originated.

Gain valuable insights with Aporia’s Explainable AI and easily share them with relevant stakeholders. Simulate “What if” situations and learn which features impact your recommendations most.

Aporia Recommender System

Look what our customers have to say about us

“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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