Swisscom implements enterprise agentic AI for customer support and sales using Amazon Bedrock AgentCore
Swisscom implemented Amazon Bedrock AgentCore to build and scale enterprise AI agents for customer support and sales operations. The solution uses a multi-agent architecture with MCP and Agent2Agent communication, AgentCore Runtime, Identity, and Memory, plus Strands Agents for development velocity, tracing, evaluation, and OpenTelemetry logging.
- Organization
- Swisscom
- Industry
- Tech & Comms
- Location
- Switzerland
- Published
- December 2025
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Swisscom
- Provider
- AWS
- Maturity
- Exploring
- Linked source
- AWS Machine Learning Blog
The solution uses a multi-agent architecture with MCP and Agent2Agent communication, AgentCore Runtime, Identity, and Memory, plus Strands Agents for development velocity, tracing, evaluation, and OpenTelemetry logging
Primary read
Use case focus
Showing 3 of 4
- 1Customer Support
- 2Sales Enablement
- 3Agentic AI
- Implemented an Amazon Bedrock AgentCore-based multi-agent architecture for personalized sales pitches and automated customer support/self-service troubleshooting.
- Integrated with Swisscom identity provider and token-based least-privilege access, with AgentCore Memory for long-term insights and AgentCore Identity for access control.
- Used Strands Agents framework, MCP, and Agent2Agent for agent/tool communication.
Architecture
Swisscom deployed customer-facing agents as containerized runtimes on Amazon Bedrock AgentCore Runtime inside a shared VPC. The design uses AgentCore Identity for inbound and outbound authentication with Swisscom's identity provider, AgentCore Memory for long-term session insights, MCP servers and Agent2Agent (A2A) for cross-agent/tool communication, and VPC endpoints/Direct Connect/Transit Gateway for private access to internal APIs and resources. The team used Strands Agents with tracing, evaluation, and OpenTelemetry for development and observability.
Sources & evidence1
- Customer explicitly identified
- Deployment status explicitly supported
- Technical implementation details available
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