Functions, Users, and Comparative Analysis
We decided that Docs should have prime location.
Build AI products you can trust.
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 […]
Fundamentals of ML observability
Metrics, feature importance and more
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 […]
4.8 out of 5 stars
We enable Responsible AI by tackling AI Hallucinations with Observability.
Aporia helps companies certify that every AI product is transparent, compliant, and aligned with business goals.
Trust takes seconds to lose and months to regain. Gain peace-of-mind with Aporia's ML observability built for teams of all sizes.
Get a unified view of all your models under a single hub. Keep an eye on model activity, inference trends, data behavior, model performance (f1 score, Precision, RMSE, etc).
Get live alerts to Slack / MS Teams on any drift, bias, performance, or data integrity issues.
Being able to identify drift is the easy part. Using Aporia you can collaboratively investigate production events, for a quick resolution.
Discover which features impact your predictions the most, and easily communicate model results to key stakeholders
Each model owner can customize Aporia to their specific use-case to ensure your models stay on track and perform at their peak.
Monitor behavior patterns, segment customers, and take action accordingly to ensure that the customers you invest in generate revenue and profits.
Boost sales and respond quickly to changes in market demand, inventory levels, and competitor pricing to ensure you’re not overpricing potential customers.
Scale recommender systems in production. Drive more revenue, increase conversions and engagement, and enhance trust in your models’ recommendations.
Ensure your Lead Scoring Model is providing its intended value so that you can nurture the leads that will actually lead your business to success.
Win back customers by increasing retention rate and accurately predicting customer churn rate with
Ensure that your Credit Risk Model performs as intended so that you can rest easy knowing that your loans are compliant, fair, and repaid (with interest, of course).
Ensure your Fraud Detection Model works as intended so that you keep the customers that generate your revenue and profit -- and ditch the bad eggs.
Improve your business's ability to capitalize on ever-changing demand and ensure that you aren't missing out on sales nor losing money on wasted inventory
Ensure your Language Models are performing as intended with real-time model monitoring, live drift alerts, and explainability.
See why Data Scientists, ML Engineers and Business Stakeholders love 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."
“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.”
“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."