ML Observability for
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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Full Visibility of Your Customer LTV in Production

Deep visibility tailored to your Customer LTV requirements. Track ROAS and see where your ad spend is generating the most value.

Segment churn prospects and optimize LTV/CAC. Truly focus on the goal of understanding what draws in your customers and how to improve their lifetime value.

Different Training & Production Datasets

Customer LTV faces a difficult prediction challenge, and with actuals ever-elusive, it doesn’t take long for issues to surface. Detect drift and track model performance with advanced ML monitoring to ensure both new and old customers remain loyal for life.

Explain & Investigate Your LTV models

Nothing is more valuable than insights into what’s attracting your high-value customers – and what’s keeping them around?

Aporia’s Explainable AI makes it easy to understand Customer LTV predictions and ensures your business can trust model predictions. Effortlessly investigate datapoints to gain insights on how to improve LTV predictions and increase profits.

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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