AI use case

Deutsche Telekom MINDR: Multi-Agent AI for End-to-End Network Operations

Deutsche Telekom and Google Cloud built MINDR — a multi-agentic system for network diagnostics and remediation spanning the full network stack. Live in Germany; scaling to Czech…

Browse catalog

At a glance

Core facts from this catalog record. Primary narrative lives in the hero above; full raw fields follow in the next section.

Company/Organization: Deutsche Telekom
Industry: Diversified Telecommunication Services
Location: Bonn

Record fields

Every column from the source row, in stable order. URLs open in a new tab.

Title

Deutsche Telekom MINDR: Multi-Agent AI for End-to-End Network Operations

Content

Deutsche Telekom, in partnership with Google Cloud, announced MINDR (Multi-Agentic Intelligent Network Diagnostics & Remediation) — a multi-agent AI system correlating signals end-to-end across network domains to proactively identify service-impacting issues and support autonomous remediation. MINDR builds on the success of RAN Guardian Agent (live in Germany since November 2025), which reduced major event management time from hours to ~1 minute (95%+ improvement), autonomously triggered 100+ remediation actions during Christmas markets, and identified 237,000 events in 2026. RAN Guardian is now scaling to Czech Republic and Croatia. MINDR uses Google Gemini models on Vertex AI and the Autonomous Network Operations framework. Specialized agents collect and correlate network data across domains, support root-cause analysis, and enable controlled remediation. The system is designed to use the A2A (Agent-to-Agent) protocol for agent coordination. Deutsche Telekom aims toward fully autonomous network operations.

URL

https://www.telekom.com/en/media/media-information/archive/mindr-ai-agents-in-the-network-1102724

Continue exploring AI deployments in the catalog.

Back to use cases