Peak launches AI Platform-as-a-Service

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High growth artificial intelligence (AI) company, Peak, has launched its AI Platform-as-a-Service (PaaS) beta programme to improve AI success rates and data scientist productivity across the enterprise.

Peak’s AI PaaS beta program sees the company’s AI System opened up to the data science and engineering community for the first time, helping enterprise users to build, train and deploy machine learning solutions across their organisations at scale.

Peak says its new AI System is a new category of enterprise technology product. The company says its AI PaaS combines the three critical components necessary for enterprise AI deployments:

1. Infrastructure: data handling, storage, compute, scaling, extensibility, security and robustness.
2. Workflow: the workflow of taking raw data, interpreting it, joining, transforming, feature extraction, model training, orchestration and deployment.
3. Solutions: easy-to-build machine learning business solutions.

A recent PWC report found that just 4% of businesses have successfully implemented AI, which is unsurprising given data scientists spend up to 80% of their time on unproductive tasks as a consequence of legacy systems. Peak’s new service aims to solve this, hoping to boost success rates by making data teams four times more productive.

Speaking at AWS re:Invent, Richard Potter, CEO of Peak, explains, “Research shows that AI projects often fail due to the complexity of deployment within the enterprise. Every enterprise must become AI-driven, yet no system is dedicated to this in the enterprise today. What’s more we know 80% of a data team’s time is spent cleaning or collecting data, data manipulation, building training sets or with feature extraction. Peak’s AI system changes that, and with it, data teams are able to focus on what they do best.”

“Legacy business systems are inflexible, slow and expensive to maintain. Data warehouses are not built to deliver machine learning solutions and data tends to exist in silos due to the proliferation of cloud applications. This all makes AI deployment challenging for many businesses.

“We’ve launched our Platform as a Service to enable teams to focus on machine learning and invest in the creation of their own machine learning solutions. Companies can then extract more value from data and experience the real benefits of AI.”