Having demonstrated much of its own AI capabilities (and successfully implementing them into its range of CRM software), Salesforce is now giving businesses the tools to build and deploy their own AI tools.
The new service, called Einstein Studio, adopts a new ‘Bring Your Own Model’ (BYOM) principle whereby companies can use their own data to power their own applications.
Customers can pull in Salesforce Data Cloud data to train models from Salesforce’s ecosystem of models, such as AWS’s Amazon SageMaker and Google Cloud’s Vertex AI.
Salesforce Einstein Studio
In its announcement, the company cites a Gartner study that found that only 54% of AI projects make it from pilot to production. Salesforce hopes to make it both more efficient and more cost-effective for companies to make their own tools this way.
Because a company can use its own data for training, it will subsequently be able to build customized and personalized interactions, boosting customer experiences and in hope, driving revenue. Linking to Salesforce also enables existing customers to get even more from their data in an era of increased focus on cost optimization.
Einstein Studio is now generally available for prospective users to try out, and the company has already provided some direction on how it could first be used.
Financial institutions, for example, could use it to create their own custom cross-selling models to help link customers to other services they may want. Similarly, the retail industry could create similar tools for recommendation, while automotive companies can predict car maintenance schedules.
Rahul Auradkar, who heads up Unified Data Services and Einstein at Salesforce, said: “Companies need quick, ROI-driven AI investments that deliver value through actionable business insights and personalized customer experiences… Now, Salesforce customers can harness their own proprietary data to power predictive and generative AI across every part of their organization.”
A Salesforce spokesperson confirmed that Einstein Studio comes as part of the Data Cloud SKU with a consumption-based billing model.
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