Fastweb + Vodafone: Redefining AIOps with predictive digital twins

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An AI-native Digital Twin platform, enabling automated, topology-aware Change Impact Analysis (CIA).

Fastweb was struggling with fragmented data, manual Change Impact Analysis (CIA), and limited network visibility. To overcome this, the telecom operator partnered with Celfocus to implement an AI-native Digital Twin that automates and accelerates CIA through a unified, graph-based view of the network, enabling faster and more informed operational decisions.

The Challenge

As part of its Autonomous Networks transformation, Fastweb faced key operational challenges:

Fragmented data and tooling landscape with multiple siloed systems
Manual Change Impact Analysis with limited automation
Lack of correlation between services, topology, and network elements
Slow decision-making, higher operational costs, and reduced visibility

These constraints significantly impacted operational efficiency and the ability to proactively manage network changes.

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The Solution

Celfocus delivered an AI-native Digital Twin platform, enabling automated, topology-aware Change Impact Analysis.

Capabilities

Unified Data Layer - Integration of multiple data sources into a single environment within Fastweb’s AWS/Databricks ecosystem.
Digital Twin - Network topology and service model built using a graph database to represent nodes, links, and service relationships.
Automated Change Impact Analysis - Graph-based engine using Celfocus algorithms to assess service and customer impact of network changes.

Benefits

Celfocus delivered a solution that operationalises an Observe - Decide – Act model, shifting Fastweb operations to an intelligent and automated approach with the following benefits: