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 […]
Experience peace of mind with an ML observability platform that diligently ensures fairness and actively mitigates bias in your AI systems.
By mitigating bias, you not only safeguard fairness in your AI but also enhance decision-making quality and build trust with users, paving the way for the ethical and responsible evolution of your technology.
Don’t wait to hear about discriminatory or unfair outcomes from your customers or the media. Tailor dashboards to showcase and track fairness metrics, ensuring your AI systems more transparent, accountable, and aligned with societal values.
This fosters trust among stakeholders and ensures that their AI contributes equitably to the betterment of all communities.
See behind the complex decision-making process of AI. Uncover features driving biased predictions and gain insights into how attributes influence outcomes.
Detailed explanations enable pinpointing sources of bias, enabling effective retraining for fairer, more transparent, and ethically sound AI systems.
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."