50% of data scientists’ time is spent on deployment—and that only gets worse with scale
AI is the future
76% of organizations prioritize AI/ML over other IT initiatives, and 64% say the priority of AI/ML has increased relative to other IT initiatives in the last 12 months.
Get to production faster
64% organization reported taking over a month to put a model in production
Buying a third-party solution costs 19-21% less than building your own
What is MLOps?
MLOps is a set of practices that combines Machine Learning, DevOps, and data engineering. MLOps aims to deploy and maintain ML systems in production reliably and efficiently. MLOps is the intersection of Machine Learning, DevOps, and Data Engineering.
How can BridgeML help me?
BridgeML will help you automate your entire Machine Learning flow and help you manage the increasing size of your dataset, reduce cost in training, set up experimentation, and automatic deployments.
What kind of services do you offer?
We use industry best practices and open-source tools to provide end-to-end AI/ML pipelines. We select the best tools that would benefit your organization specifically, package them in automated pipelines. We don’t reinvent the wheel, we enable re-use of infrastructure across your entire organization.