Vidora team

Our Journey

We started Vidora in 2013 because we noticed that while many businesses wanted to embrace machine learning, most were daunted by the challenges of starting from scratch. Though machine learning promised to change the game, the up-front costs of time, price and technical training just seemed too high. That’s why we created Cortex, the No Code Machine Learning Platform that is truly accessible to anyone in any organization.

Today, Vidora is based in San Francisco and works to place ML at the heart of some of the world’s largest businesses, such as News Corp, Walmart and Discovery.

Our Founding Team

Alex Holub


Alex studied artificial intelligence throughout his academic career at Cornell University and during his Ph.D. at Caltech. He has published over 15 academic papers and holds numerous patents in the areas of machine learning, computer vision, and artificial intelligence. Prior to co-founding Vidora, Alex was a technical and product management lead at Ooyala.

Abhik Majumdar


Abhik is responsible for the roadmap and build out of Vidora’s technology platform. He graduated from IIT and UC Berkeley with a Ph.D. in Electrical Engineering, Computer Science, and Information Theory. Abhik’s work has been published and featured in over 20 journal and conference articles. Before Vidora, he was a staff engineer and technical lead at Ooyala and an instrumental part of developing the first generation Flip Video camera.

Philip West

Head of Product

Philip graduated with a bachelors in Computer Science from Stanford where he was part of the NCAA Champion Track team. At Stanford, he learned about product, human computer interaction, and design, which helped him start his entrepreneurial journey. After graduation, Philip joined Affinity Circles as a technical co-founder. Later, he joined Ooyala, as one of the first engineers where he helped build and grow the initial video platform and team before its acquisition.

See How Vidora Works

See how we’re helping some of the world’s largest businesses automate their machine learning solutions in a fraction of the time it would take to do themselves.