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Salesforce And AWS Partnership

The Strongest Partnership

Thanks to Hyperforce, Salesforce will increase its use of AWS’s computing, storage, data, and AI technologies, allowing the company to improve already popular offerings like Salesforce Data Cloud. AWS will also make more use of Data Cloud and other Salesforce products. With Data Cloud, AWS can consolidate all of its client information into one cohesive profile, paving the way for more tailored service.

The long-standing worldwide strategic collaboration between Salesforce and AWS has just become even stronger. The two companies have announced new product integrations spanning data and AI, and for the first time, you can buy some Salesforce goods on the AWS Marketplace. With the new agreement in place, companies may more easily integrate cutting-edge generative AI technologies into their apps and processes while also maintaining the safety and security of their data as it moves between Salesforce and AWS. Companies will further integrate AWS and Salesforce products to make it easier for clients to take advantage of the combined value of both platforms.

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As part of their open model ecosystem goal, Salesforce will now enable Amazon Bedrock, a fully managed solution that makes foundation models (FMs) available through a single application programming interface (API) from major AI businesses. Thanks to the Einstein Trust Layer, this will enable Salesforce AI-driven apps and processes to access Amazon Bedrock.

Furthermore, Salesforce Data Cloud will grow to include data exchange across other AWS technologies. New centralized access controls will regulate these Data Cloud connections, allowing customers to manage secure user access for Data Cloud material stored in Amazon Simple Storage Service (S3) at the folder, object, and file levels.

What Is the Einstein Trust Layer?

Integral to the Salesforce Platform from the start is the Einstein Trust Layer, a safe artificial intelligence architecture. Featuring state-of-the-art security measures throughout our products and policies, the Einstein Trust Layer is built on Hyperforce for data residency and compliance. The Einstein Trust Layer enables teams to take advantage of generative AI while protecting their customers’ data, thanks to its design for enterprise-level security requirements.

Read: How should CFOs approach generative AI

Let’s Check- What’s Trending?

Making Subscribing and Managing Salesforce Offerings Even Easier for AWS Customers: Salesforce is now making its products available on the AWS Marketplace. This includes Data Cloud, Service Cloud, Sales Cloud, Industry Clouds, Tableau, MuleSoft, Platform, and Heroku.

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By combining their respective data management systems, AWS and Salesforce are creating Data Cloud, a robust, adaptable, and secure SaaS data platform that will improve customer experiences.

With AWS, customers can easily exploit p*********** budgets and boost company performance thanks to a unified view of their IT spending, streamlined procurement procedures, and customizable choices like private pricing and consolidated b******. In the United States, joint customers may already buy several Salesforce goods through AWS Marketplace. In 2024, they want to increase product and geographical support.

Protected Through the integration of AWS Data and AI Services into Salesforce’s Einstein 1 Platform, new solutions such as Salesforce Prompt Builder, which is a component of the Einstein Copilot Studio, will enable customers to develop personalized prompt templates based on their data. Data Cloud is powered by AWS compute services like Amazon Elastic Compute Cloud (EC2), Amazon Elastic Kubernetes Service (AKS), and AWS Lambda. Customers can safely run their code for data processing tasks like complex transformations, calculated insights, data triggers, or user-defined functions.

Prominent models housed on Amazon Bedrock are among the FMs that can receive personalized prompt templates. Customers can safely utilize retrieval-augmented generation (RAG) approaches with models from top AI firms including Stability AI, Amazon, Anthropic, Cohere, and AI21 Labs. Data Cloud and Amazon SageMaker integration gives developers access to their FMs; the Einstein Trust Layer allows them to fine-tune FMs on Amazon Bedrock; and the Salesforce Customer 360 platform powers generative AI experiences. Developers can also use simplified tooling for this purpose.

Read: AI And The Future

What’s More In Line?

Improving the Salesforce Service Cloud Omnichannel supervisor experience, AWS and Salesforce are integrating Amazon Connect Chat into Service Cloud Digital Engagement, Service Cloud Voice and Amazon Connect, and Amazon Connect for capacity planning, agent scheduling, and forecasting.

This will lead to seamless customer service. A unified customer experience, more productive agents across channels, and more informed supervisors will be made possible by this, in addition to integrated generative AI capabilities that power unified customer insights and both agent and management automated help. We expect to provide the first phase of this deeper integration in early 2024.

Across resource-heavy workloads, including development with FMs, Heroku clients will have access to the most performant and cost-effective infrastructure. Heroku now offers Amazon CodeWhisperer, which helps users create apps quicker and with higher security. A new AI-first design for cross-platform process automation can be created by Salesforce developers using Einstein Copilot Studio. These actions may be invoked by Einstein Copilot and can cover a wide range of scenarios, from Salesforce processes to AWS services.

New AWS Compute and Development Services for Developers: In the first half of 2024, Salesforce and AWS will redefine Heroku as the Platform-as-a-Service (PaaS) layer, allowing developers to build AI-first apps on both platforms. Using the most powerful and cost-effective AWS infrastructure, Heroku will enhance its Dyno compute capabilities. This includes accelerated Amazon EC2 instances powered by Nvidia GPUs, AWS Trainium, and AWS Inferentia for ML training and inference, and additional GPU-optimized EC2 instances for graphics-intensive applications. For the optimal price-performance compute, they will also utilize EC2 instances that are based on AWS Graviton.

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[To share your insights with us, please write to sghosh@martechseries.com]

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