The most advanced ML Observability platform
We’re super excited to share that Aporia is now the first ML observability offering integration to the Databricks Lakehouse Platform. This partnership means that you can now effortlessly automate your data pipelines, monitor, visualize, and explain your ML models in production. Aporia and Databricks: A Match Made in Data Heaven One key benefit of this […]
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We’re excited 😁 to share that Forbes has named Aporia a Next Billion-Dollar Company. This recognition comes on the heels of our recent $25 million Series A funding and is a huge testament that Aporia’s mission and the need for trust in AI are more relevant than ever. We are very proud to be listed […]
Scale your recommender systems in production. Drive more revenue, increase conversions and engagement, and enhance trust in your models’ recommendations.
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.
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 [email protected], [email protected], [email protected], and easily running an array of behavioral tests specific to your recommender systems.
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.
See why data scientists, ML engineers, and R&D love using Aporia.
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.”
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.”
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.”
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.”
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.”
“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.”
