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DataRobot aims to tackle GenAI problem with Enterprise Suite
The AI and machine learning vendor's new platform provides customizable applications and agents to help enterprises profit from their GenAI investment.
DataRobot's new Enterprise AI Suite is designed to help enterprises develop generative AI applications that meet business needs.
Introduced on Nov. 12, Enterprise AI Suite provides organizations with tools to install and run their GenAI applications.
The suite includes composable AI applications and agents that teams can build on for different use cases.
It also includes a generative AI application workshop developers can use to build custom generative AI application interfaces. A new API framework enables developers to visualize, work with and save AI pipelines.
Finding ROI
With the new suite, DataRobot seeks to address the problem enterprises face when building out individual components for each generative AI application they plan to roll out.
"This is actually a pretty big problem for enterprises," Futurum Group analyst Keith Kirkpatrick said. "This requires significant expertise and time, which usually equates to hiring an outside AI consultant or developer."
However, a skills shortage makes it hard for enterprises to hire outside developers, said IDC analyst Ritu Jyoti.
"Organizations can accelerate time to value by kickstarting their efforts with prebuilt components that can be customized further," Jyoti said.
Having prebuilt components lets internal developers focus on customization, enabling enterprises to achieve ROI more quickly, Kirkpatrick said.
It also lets internal developers focus on important tasks such as testing and managing technology updates, he added.
DataRobot is not the only vendor hoping to help enterprises address this issue.
Other large SaaS vendors, such as Salesforce, also offer customization tools. For example, Salesforce has its Einstein AI tools.
However, what makes DataRobot stand out is the vendor's experience in developing AI technology modularly so that it is easily integrated into different types of workflows and industry-specific applications, Kirkpatrick said.
"They are also well positioned to appeal to organizations that want to deploy agnostic AI tools that will work across their entire application stack, even if they use a wide variety of vendors and applications," he added.
Challenge and other releases
However, the challenge DataRobot faces is convincing enterprises that it can produce results faster than its competitors, Kirkpatrick continued.
DataRobot will deliver value with the Enterprise Suite in 30 days, the vendor claimed.
"It will be interesting to see if that promise meets reality," Kirkpatrick said.
DataRobot also introduced an add-on AI observability tool and one-click compliance documentation and testing for businesses to stay compliant with different regulations and policies. The AI vendor also introduced large unstructured data preparation and handling tools to help enterprises speed up generative and predictive AI development.
The tools help enterprises accelerate AI-ready data preparation, generate high-quality RAG outputs and scale and optimize costs, according to DataRobot.
Esther Ajao is a TechTarget Editorial news writer and podcast host covering artificial intelligence software and systems.
