Explainable AI For Your ML Models

Drive business impact with transparent and explainable AI. Get started in minutes with Aporia’s ML monitoring and explainability solution.

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Explainability for the Whole Team & More

With Aporia’s advanced Explainable AI toolbox, you can understand the ‘Why’ behind your ML model predictions. Discover which features impact your predictions the most, and easily communicate model results to key stakeholders. Using XAI, you can also simulate “What If” scenarios to see how they will affect your model.

Business User
Data Scientist
ML Engineer
Data Analyst
Auditor

Get to the Root Cause

Find the root cause of any issue and discover when it started using our Data Points and Time Series Investigation Tools.

Aporia makes it easy to slice and dice your data to quickly drill down into your model’s data points and the impact on prediction results.

Investigate & Debug Your Models

With Aporia, you can analyze how your models arrive at their predictions, understand how a change in a feature impacts a prediction, and prevent issues like bias and drift in the future.

Use our Data Point Explainer to debug your data at a specific point, and then re-explain in one click.

A Simple Explanation for Everyone

Ensure that all key stakeholders trust your model’s results and outputs with easily explainable model predictions that can be shared in seconds.

Loved By

See why data scientists, ML engineers, and R&D love using Aporia.

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

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