Spell – A Streamlined Machine Learning Platform
Meet Spell – data science and machine learning startup that raised 15M$ to bring AI and deep learning to the global workforce.
|Revenue: unknown||Location: New York|
|Founded: 2017.||Specialties: Artificial Intelligence, Computer, Machine Learning, Software|
Spell is an end-to-end data science and machine learning platform that provides the infrastructure for companies and developers to prepare, train, deploy, and manage the full life-cycle of Machine Learning and Deep Learning experiments. Moreover, Spell was developed to streamline the MLOps process. Founded in 2017 by former Facebook engineer Serkan Piantino and Trey Lawrence, the company was born out of a desire to empower and transform the global workforce by making deep learning and AI accessible to everyone. It is an ideal solution for those looking to run multiple experiments in parallel and get fast results without worrying about overhead or infrastructure management.
How it works?
With Spell, the newest GPUs from Nvidia and Google are virtually available for anyone to run their tests. Individual users can get on for free, specify the type of GPU they need to compute their experiment and simply let it run. On the other hand, corporate users are able to view the runs taking place on Spell and compare experiments, allowing users to collaborate on their projects from within the platform. Furthermore, enterprise clients can set up their own cluster, and keep all of their programs private on the Spell platform, rather than running tests on the public cluster.
Spell also offers enterprise customers a “spell hyper” command that offers built-in support for hyper-parameter optimization. Users can track their models and results and deploy them to Kubernetes/Kubeflow in a single click.
Perhaps most importantly, platform allows an organization to instantly transform their model into an API that can be used more broadly throughout the organization, or used directly within an app or website.
The implications here are huge. Small companies and startups looking to get into AI now have a much lower barrier to entry. Likewise, large traditional companies can build out their own proprietary machine learning algorithms for use within the organization without an outrageous upfront investment.
Individual users can get on the platform for free. Also, company have Teams and Enterprise plans. Their charges are based on the concurrent usage, so if the customer has 10 concurrent things running, the company considers that the “size” of the Spell cluster and charges based on that.
Spell raised 15M to bring AI to global workforce.
Last year company announced $15 million in funding, led by Eclipse Ventures and Two Sigma Ventures. This investment will be used to incorporate more advancements and power even larger organizations, while continuing to bring AI and deep learning to more of the global workforce.