Machine Learning gets your models into production. With services across the full ML lifecycle, our experienced data scientists and engineers help you build, train, and deploy ML models, then ensure those models continue delivering value — without requiring you to build your own team of expensive ML specialists. And with our enterprise-tested MLOps Framework, you’ll have a repeatable process to systematically train, deploy, and monitor systems of models, track experiments, and scale your innovations.
We provide the resources and expertise you need to handle use case discovery, feature engineering, model training, validation, and everything in between.
We bring the expertise you need to scale and harden trained models, then integrate them with business systems and pipelines — building with an automated, cloud-centric approach to deploy faster, more reliably, and at lower costs.
We offer architecture and 24/7/365 proactive monitoring and alerting of model performance, data quality, and application/platform health — taking action to refit models and remediate issues before they adversely impact the business.
We provide an enterprise-tested MLOps framework and automated workflow to put your machine learning models into production faster, more efficiently, and with less risk. By replacing manual, ad-hoc processes with an automated, opinionated “assembly line” to train, deploy, monitor, and secure machine learning models, you empower your teams not only to build innovative new capabilities, but to deliver those innovations at-scale.
A top-5 U.S. restaurant chain, already doing $10+ billion in annual sales, knew that to sustain their aggressive growth trajectory, they needed to continue making good on their core brand promise: delivering exceptional quality and customer service at a competitive price. They weren’t historically a tech-focused company. But to ensure consistency across several hundreds of restaurant locations, they needed to become one.
Our team of data scientists and machine learning engineers helps you build out a repeatable architecture with process and automation to train, deploy, and monitor systems of models; track experiments; and ultimately scale your innovations.
With phData, you get both the data science and engineering support you need — at every stage of the machine learning lifecycle.
Learn how phData can help solve your most challenging data analytics and machine learning problems.
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