Singapore – Amazon Web Services (AWS) and Salesforce have expanded their collaboration with a series of integrations aimed at connecting artificial intelligence (AI) agents, enterprise data and customer workflows across their platforms.
The companies said the updates are intended to address several challenges in enterprise AI adoption, including accessing customer relationship management (CRM) data outside CRM applications, connecting data across cloud environments without moving it, and extending AI agents into areas such as real-time voice and team collaboration.
The new integrations include Salesforce business context in Amazon Quick, AWS frontier agents in Slack, expanded zero-copy data access across AWS services, broader model choice for Salesforce Agentforce through Amazon Bedrock, and interoperability between Agentforce Voice and Amazon Connect Customer.
The companies said the changes will allow teams to use capabilities across existing workflows. For example, sales teams can use Amazon Quick to prepare for meetings using live CRM data, while service teams can route customer issues between Agentforce and Amazon Connect Customer.
“Salesforce’s business context creates value everywhere our customers work. Trusted data now reaches into the surfaces teams rely on daily, and our collaboration with AWS extends that reach even further, all with governance built in every step of the way,” said Nick Johnston, EVP for Global Partnerships at Salesforce.
“The further that context reaches, the more valuable it becomes. That’s what turns AI from a feature in one app into how enterprises actually get work done,” Johnston continued.
“The companies moving fastest and delivering differentiation with AI are the ones building on their own data, with the applications and cloud infrastructure they already trust. That’s why removing the friction between environments matters,” said Rahul Pathak, VP of Data and AI GTM at AWS.
“These new integrations with Salesforce give customers data access without migration, model choice at the right economics, and AI agents where their people already work. When enterprises can do all of that seamlessly, AI becomes how they actually operate and drive business outcomes, not just something they’re piloting,” Pathak continued.
AI agents across enterprise workflows
Salesforce business data, context and skills are now available through Amazon Quick without requiring custom integration. This enables users to access information such as pipeline health, account summaries, service cases and operational analytics within Quick.
The integration uses the Model Context Protocol (MCP) open standard and Salesforce’s headless architecture to connect the two platforms. Salesforce said this can allow teams to bring information such as deal status, service cases and recent customer activity into a single meeting brief.
AWS is also bringing its frontier agents into Slack, beginning with AWS DevOps Agent. AWS Security Agent, AWS FinOps Agent and AWS Partner Central agents are expected to follow in autumn 2026.
The agents can operate within Slack conversations, allowing teams to investigate incidents or review security findings without switching to a separate AWS console.
Agentforce customers can also access a wider selection of foundation models through Amazon Bedrock, including models from Anthropic and NVIDIA. OpenAI models, which are already generally available through Amazon Bedrock, are expected to become available in Agentforce.
AWS said Amazon Bedrock enforces Zero Data Retention, while Salesforce’s Trust Layer provides capabilities including dynamic grounding and toxicity detection. The companies said the combined approach supports governance requirements for regulated industries, including HIPAA, PCI, SOC 2 and ISO 42001 compliance.
“At DXC Technology, we manage complex enterprise environments for customers across every major industry, with Salesforce as a central system of record for sales. Amazon Quick’s agentic capabilities have become an integral part of how our teams operate,” said Russell Jukes, Chief Digital & Information Officer at DXC.
“With more than a dozen AI agents already deployed and growing, our consultants and delivery teams are pulling customer data, surfacing insights, and acting on opportunities faster than ever, all without leaving the tools they work in every day. We see tremendous potential in the Amazon Quick and Salesforce integration to drive productivity at scale, both internally and for the customers we serve,” Jukes continued.
“Having access to the broad selection of foundation models in Amazon Bedrock through Agentforce gives us the flexibility to choose the right model for each use case — helping our teams build smarter AI agents that deliver better outcomes for our customers,” said Joshua Stern, Director of GTM Systems at Engine.
“A lot of our engineering work and conversations already happen in Slack. Bringing the AWS DevOps Agent into those conversations allows my teams to spot and resolve issues in their development environments faster, without breaking their flow. That helps us move more quickly and ultimately get products in front of our customers sooner,” said Muddassar Shaikh, Senior Vice President of Engineering at GoodRx.
“We are excited to work with AWS and Salesforce to help shape this experience. The value we’re seeing from the AWS DevOps Agent and Slack integration is not just in triggering investigations, but in creating a shared workspace where engineers can collectively direct, refine, and act on the results,” said Giriraj Jain, VP of Engineering Services at Quicken Inc.
“Having those capabilities embedded in an environment our teams use every day has the potential to streamline how incidents are understood and resolved,” Jain continued.
Connecting enterprise data without migration
The expanded integrations also extend zero-copy data access between Salesforce and AWS, allowing AI agents to work with enterprise data without requiring organisations to migrate or duplicate information.
Salesforce Data 360 zero-copy capabilities now extend to AWS Glue-managed Apache Iceberg tables, S3-backed Apache Iceberg tables, Amazon Aurora, Amazon RDS and SageMaker Lakehouse. The expansion builds on existing support for Amazon Redshift and Amazon S3 with private connectivity.
Salesforce and AWS are also exploring bidirectional semantic-information sharing with the AWS Glue Data Catalog. The companies said this work could support more connected data and AI experiences while reducing the need for data movement.
Separately, Informatica is expanding the general availability of its MCP servers to support enterprise use cases involving platform administration, catalogue discovery and enrichment, data-quality scores and master-data retrieval.
The integrations can be accessed through Amazon Bedrock AgentCore and Amazon Quick, allowing organisations to connect AI agents with governed enterprise data.
AI-enabled voice and collaboration
The collaboration also extends to voice-based interactions. Salesforce and AWS are introducing Agent2Agent (A2A) support between Agentforce Voice and Amazon Connect Customer, enabling the two platforms to communicate through real-time, bidirectional audio over WebSockets.
The companies said the integration is designed to allow AI agents across the two platforms to coordinate during voice interactions.
Salesforce AI Research has also worked with AWS to optimise Salesforce’s proprietary speech models on AWS Trainium chips for voice dictation in Slack.
The capability is designed to provide low-latency transcription within Slack threads, allowing users to capture and share information through voice. Salesforce said optimising the models on AWS’s purpose-built silicon can reduce inference costs.
Expanding the AWS-Salesforce relationship
The announcements build on a decade-long relationship between AWS and Salesforce covering cloud infrastructure, data and enterprise applications.
Salesforce Clouds are now available through AWS Marketplace in 33 countries. Eligible AWS spending commitments can be applied towards Salesforce products, including Agentforce, allowing customers to consolidate procurement and billing.
The latest integrations reflect a broader enterprise AI trend towards connecting AI agents with existing applications, data environments and workplace collaboration tools rather than deploying them as separate workflows.
The new capabilities are being introduced on different schedules. Amazon Quick with Salesforce’s headless architecture, Agentforce model choice through Amazon Bedrock, Data 360 zero copy expansion, Informatica’s headless expansion and Slack voice dictation are available now. AWS DevOps Agent is available in Slack, with additional AWS agents expected in autumn 2026, while Agentforce Voice and Amazon Connect Customer interoperability is planned for autumn 2026.
