Enabling Self-Service MLOps and Faster ML Delivery at monday.com

Monday.com, a work operating system (Work OS) that allows organizations to manage every aspect of their work, faced significant challenges in implementing machine learning (ML) solutions. The company's data team, BigBrain, was responsible for the data and analytics platform and ML initiatives. However, as demand for ML solutions grew, the data scientists found themselves heavily reliant on engineers to bring models to production. This resulted in a high time to value, with models often waiting for deployment until a developer was available to set up the infrastructure. Furthermore, the data scientists were siloed and had a disconnected workflow between where the model was trained, deployed, and monitored, creating unnecessary complexity. Key pain points included excessively high time to value due to production bottlenecks, dependency on developers and engineers for deployment, missing critical MLOps capabilities, inability to consolidate distinct endpoints into a multi-model endpoint pattern, and disjointed workflow due to each data scientist working with different machine learning tools.

Monday.com is a work operating system (Work OS) that allows organizations of any size to create the tools and processes they need to manage every aspect of their work. The platform intuitively connects people to processes and systems, empowering teams to excel in every aspect of their work while creating an environment of transparency in business. Monday.com has teams in Tel Aviv, New York, San Francisco, Miami, Chicago, London, Kiev, Sydney, São Paulo, and Tokyo. The platform is fully customizable to suit any business vertical and is currently used by over 152,000 customers across over 200 industries in 200 countries.