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U Mobile uses Amazon Bedrock AgentCore to cut telco support tickets by 84.5 percent

U Mobile, Malaysia’s newest 5G provider, built AiDaH, an AI-driven agentic helpdesk on Amazon Bedrock AgentCore, to slash operational friction. The platform automates cross-system diagnostics—checking logs, querying APIs, and retrieving policies—so support agents spend less time on manual lookups and more on human decision-making. AiDaH now handles over 150 documented operational scenarios…

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Key points

  • U Mobile built AiDaH on Amazon Bedrock AgentCore to automate cross-system diagnostics, cutting ticket volumes by up to 84.5 percent internally
  • Six-layer architecture integrates with Microsoft Teams, AWS Lambda, and on-premises systems via encrypted VPN tunnels for secure access
  • Platform uses Agent2Agent protocol for specialist collaboration, MCP for universal tool connectivity, and spec-driven development in Kiro to scale

The project began in late 2025 with two pilot agents and Amazon Bedrock Knowledge Bases, evolving into a six-layer architecture by mid-2026. U Mobile’s Information Systems Division (ISD) partnered with AWS and AWS Partner Axrail to design a platform prioritizing reach (real-time cross-system coordination), depth (multi-step root cause analysis), and community (secure multi-tenant access with role-based controls). The team used spec-driven development in Kiro, AWS’s agentic IDE, to standardize tool integrations via the Model Context Protocol (MCP). This approach let them scale from two use cases to 150+ scenarios in under a year, with 8 agents deployed by Q3 2026 to 50 L2 call center and branch users. Adoption surged after AiDaH became part of U Mobile’s L2 support standard operating procedures, with staff rating it 4.6/5 for ease of use.

Full story from AWS Machine Learning Blog · by Jin Tiong Lim primary sourceOpen source ↗

How U Mobile built agentic telco operations with Amazon Bedrock AgentCore

AWS Machine Learning Blog · 4 November 2026

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This text was published by AWS Machine Learning Blog and written by Jin Tiong Lim. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

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The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.

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