Details
- AWS and Salesforce announced an expanded collaboration in September 2026, introducing new AI and data integrations that link Salesforce CRM context with Amazon Quick, Slack, Bedrock, and Amazon Connect Customer without requiring data migrations.
- The update involves Salesforce, Amazon Web Services, Slack, Informatica, and enterprise customers such as DXC Technology, Engine, GoodRx, and Quicken, along with model providers Anthropic and NVIDIA and forthcoming OpenAI access via Amazon Bedrock.
- Key technical changes include native access to Salesforce pipeline, account, and service data in Amazon Quick via Salesforce’s headless, MCP-based architecture; AWS frontier agents (starting with AWS DevOps Agent) embedded in Slack; and Agentforce access to a broad set of Bedrock foundation models with Zero Data Retention and Salesforce’s Trust Layer for governance and compliance.
- Data 360 Zero Copy now extends across AWS Glue-managed and S3-backed Apache Iceberg tables, Amazon Aurora, Amazon RDS, SageMaker Lakehouse, Redshift, and S3 with private connectivity, while Informatica expands MCP-based headless services for administration, catalog discovery, data quality, and master data to Amazon Bedrock AgentCore and Amazon Quick.
- On the voice side, Agentforce Voice and Amazon Connect Customer gain real-time, bidirectional Agent2Agent orchestration over WebSockets slated for Fall 2026, and Salesforce AI Research has optimized proprietary speech models on AWS Trainium to enable low-latency, lower-cost voice dictation in Slack; key features are largely available now, with some agents and voice orchestration rolling out in Fall 2026 and Salesforce Clouds purchasable via AWS Marketplace in 33 countries.
Impact
By embedding AI agents and CRM context directly into Amazon Quick, Slack, and voice channels, AWS and Salesforce are accelerating agentic workflows on top of existing enterprise infrastructure, lowering adoption friction and strengthening cross-cloud data governance. Over the next 12–24 months, these zero-copy and multi-agent capabilities are likely to shape R&D roadmaps around interoperable AI agents, drive spend consolidation through cloud marketplaces, and intensify competition in enterprise AI platforms that emphasize compliance-ready, multi-model orchestration.
