New Bring Your Own Lake integrations enable secure sharing of unified customer data from Salesforce Data Cloud to a broad set of AWS data and AI services; Data Cloud customers can access data from Amazon Redshift and Amazon data lakes on AWS without moving data
Customers can now leverage Amazon Bedrock securely within Salesforce Einstein Copilot Studio to build generative AI powered skills, apps, and experiences across the Salesforce Customer 360
Salesforce and Amazon Web Services (AWS) today announced an expanded partnership for new Bring Your Own Lake (BYOL) and Bring Your Own Large Language Model (BYO LLM) integrations between AWS and Salesforce Data Cloud. Data Cloud is a hyperscale customer data platform that lets companies unify all their Salesforce data with vast amounts of engagement data from external sources to create harmonized and unified customer profiles.
These integrations build on AWS and Salesforce’s existing generative AI partnership, allowing customers to seamlessly and securely unify their data across Data Cloud and AWS services like Amazon Redshift, Amazon EMR, and Amazon SageMaker, to leverage the broad set of foundation models available in Amazon Bedrock securely within the Salesforce Platform. Customers can now safely infuse the latest generative AI technologies from AWS into their applications and workflows through the Einstein Trust Layer.
Why it matters: As AI adoption surges, 73% of business leaders agree that data helps reduce uncertainty and make more accurate decisions in business conversations. However, 33% report they lack the ability to generate insights from data. With this expanded partnership, organizations can bring their data together in one place, making it easier to store, manage, and scale while reducing costs. And, with new AI integrations, companies can power their AI applications with their own models from both AWS and Data Cloud to efficiently provide smarter, personalized customer experiences.
New integration capabilities include:
- BYOL support for AWS: Customers can easily and seamlessly unite all of their data across Salesforce and AWS for better, faster insights, predictions, and more from their existing data processing pipelines from Data Cloud. And with zero Extract, Transform, Load (ETL) processes, customers can securely unite this data without copying or moving it.
- BYOL Data Federation will allow customers to access data from Amazon Redshift and Amazon data lakes within Data Cloud without having to move the data first, enabling a unified profile across clouds.
- BYOL Data Sharing will allow customers to securely share and use unified customer data from Data Cloud across many AWS services, including Amazon Redshift, Amazon SageMaker, Amazon EMR, Amazon Athena, and more.
- BYO LLM with Amazon Bedrock: Customers can bring LLMs they have hosted in Amazon Bedrock to power generative apps in Salesforce while maintaining their security and data compliance requirements. The companies will also integrate Amazon Bedrock with Salesforce’s Einstein Trust Layer, allowing Salesforce customers to securely use their CRM data to fine-tune LLMs from Amazon or other AI providers like Anthropic, Cohere, AI21 Labs, and Stability AI and use them across the Salesforce platform.
With this partnership:
- With BYOL Data Federation, a media company can create a true unified customer profile in Data Cloud that spans their customer support center, marketing teams, and global ecommerce sites joined securely with petabyte-scale streaming and mobile app data stored in one or more data lakes on AWS. They can then activate these unified profiles across every touchpoint with the customer to help recommend the right products or services, or personalize every customer engagement.
- With BYOL Data Sharing, a financial institution can securely share their unified customer data from Data Cloud with Amazon SageMaker to train a custom AI model to predict a banking customer’s likelihood to engage with a new service offering, and use that model to send the right personalized message to the customer.
- With BYO Large Language Model, a manufacturer could bring their own foundation model securely fine-tuned on Amazon Bedrock to Einstein to build generative AI-powered applications and skills that make their sales reps more productive, or improve their service agents’ customer engagements.
Go deeper: This news builds on existing integrations between Einstein and Amazon SageMaker, which allow customers to easily use models they’ve trained and deployed (including LLMs) on Amazon SageMaker to power predictions across the Salesforce Customer 360. In addition, Service Cloud Voice with Amazon Connect delivers a differentiated and seamless contact center solution leveraging Salesforce’s industry-leading agent desktop integrated with services from AWS, including Amazon Connect, Amazon Comprehend, and Amazon Transcribe, which can help improve agent productivity and customer experience across voice and digital channels with an all-in-one, AI- and ML-powered contact center.
- These integrations will be in pilot for customers next year.