Between 80% and 90% of all models developed by data scientists never make it to production. Using our extensive repository of pipelines and expertise, we design machine learning operations that enable you to operationalize your AI aspirations and extract more value from your data. Faster.
Making sense of your data
You’re drowning in vast volumes of data. You know within this data lies insight that could be instrumental in helping you to distribute your products in more efficient ways, for validating pricing strategy, or preventing lost sales and churn. But how do you operationalize AI and unlock this value potential? The answer lies in our machine learning operations (ML-Ops) solutions.
Making your data deployable
Does your use case require batch processing or real-time streaming? Would federated learning work best or is a centralized approach sufficient? And then there’s security, regulations, your existing IT landscape and the size and maturity your engineering workforce to consider. You can’t develop MLops in isolation. We work with your C-suite and within your teams to design solutions tailored to your unique use cases and your organization's maturity level.