Machine Learning algorithms are now commodities. ML models allow businesses to dramatically improve performance and reduce risk — that’s why they invest to build and train those models accordingly. It’s a challenge to manage a model in production. In addition to “regular” applicative challenges — most models degrade over time — there are few best practices or common stakeholders. The challenges only amplify when companies begin to run multiple models.
Qwak is a management platform designed specifically for machine learning models in production. The platform allows all relevant stakeholders to observe, analyze and manage their ML models regardless of how they were developed, deployed or hosted. With Qwak, you can quickly onboard your models with a single line of code. Qwak supports and assists R&D leaders, data scientists, DevOps engineers, technical analysts, and product owners by providing a management and observability platfrom with a clear view for each model. Everyone sees the model from an infrastructure level to the business outcome level, with complete metrics, performance, costs and versions.
We are a founding team of ML, cloud and data experts (ex AWS, WIX, IronSource & Payoneer) who experienced the growth of machine learning models in production both as customers and as a cloud vendor. Understanding the value, needs, requirements and gaps led us to build a management layer that helps clients focus on building their company rather than juggling an increasing load of models.