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 alongside other technological trailblazers, such as Ermetic, Justt, Aidoc, Overwolf, Torq, TytoCare, Balance, StreamElements, and Datagen. Many of these companies, and the ones to come, rely on Machine Learning, and therefore require the ability to monitor 🔍 and explain their models in production. Making our solution essential to the efficient and responsible deployment of next-gen innovation. Read the full article 👉 here.
Building Trust in AI with ML Observability
The MLOps space is maturing fast. As more and more companies leverage AI by integrating ML Models into a wide range of business applications and processes, a growing need for ML Observability has emerged.
This, in addition, to the Forbes recognition, further cements Aporia as a game-changing company that empowers businesses to put Responsible AI into practice. We are amazed by the tremendous growth 💪 that we have experienced since launching our self-serve platform in 2021, and grateful for the overwhelmingly positive reception 🤗 we’ve received from the MLOps community. At the same time, we acknowledge that our work is far from complete.
Our journey began with an understanding that in an ever-evolving reality, ML teams need fast-paced, reliable, and customizable tools to ensure that their models are performing at their best. Over the past couple of years, we’ve worked side-by-side 🤝 with Data Scientists and ML Engineers to build and optimize an end-to-end ML Model Observability platform that enables them to monitor, explain and improve 📈 their models in production.
We have entered into a new era, where humanity has millions of touchpoints with machine learning models on a daily basis. While this may be the catalyst to help society leap forward, it is crucial to have effective guardrails like Aporia that keep unintentional bias & fairness ⚖️, model degradation, and other ML issues, in check. This, in turn, will allow data science and ML teams to continue shooting for the stars 🚀 with their models by creating AI that improves our lives every day.