Login
Register
Fragmented and inaccurate inventory data is a major barrier to autonomous networks. This Catalyst uses AI, automation and digital twins to create a reliable, real-time network view.
If your inventory is wrong, your network decisions are wrong
Accurate network inventory is fundamental to telecom operations, yet many CSPs still rely on fragmented records spread across multiple systems. This creates an incomplete view of network assets, services and their relationships, forcing teams to spend time on manual data collection, validation and updates.
The consequences are operational and commercial. Poor data quality slows fault resolution because teams cannot quickly identify the location or cause of an issue. It also increases OpEx, undermines SLA performance and weakens customer trust when service restoration or order delivery is delayed.
As operators move toward autonomous networks, these challenges become more urgent. Automation depends on trusted, current and complete data. Without a robust approach to intelligent inventory reconciliation, operators risk automating decisions based on unreliable information.
The Catalyst, Agentic network resilience and lead to quote using AI-driven digital twin, introduces an AI-driven, end-to-end inventory management foundation that brings together autonomous reconciliation, cognitive inventory assurance, a conversational inventory assistant and digital twin-based what-if simulation.
At its core is a living cognitive network twin powered by agentic AI. By using active, complete and accurate network data, the solution helps operators understand the current state of hybrid networks, predict discrepancies and assurance risks, and test operational responses before acting in the live environment.
The project uses TM Forum Open APIs and ODA components, including TMFC001, TMFC008, TMFC012, TMFC037, TMFC038, TMFC043, TMFC045, TMFC046 and TMFC062, to support a more modular and standards-based approach to inventory, assurance and service operations.
The demonstration focuses on practical scenarios including autonomous network resilience during natural disasters and proactive service evolution for complex enterprise services, such as improving the lead-to-quote experience for banks.
The business impact is designed to be measurable. The Catalyst targets a 60% reduction in the time required to reconcile inventory across hybrid networks, an 85% improvement in accuracy when predicting discrepancies and assurance risks, and a 40% decrease in SLA breaches and order fallout rates.
For operations teams, the AI inventory assistant is intended to provide actionable insights in three seconds, helping them move from manual investigation to faster, more proactive decision-making. For customers, this can translate into more reliable services, faster restorationand greater confidence in the network.
The wider value is resilience. By combining predictive assurance with digital twin simulation, operators can model the impact of major incidents or natural disasters, assess options and respond before service quality is affected.
Darwin Janz, Senior Planner Technology Strategy at SaskTel, said the project reflects a long-standing industry challenge: “CSPs are operating with errors and inconsistencies in inventory records,” caused by more than a century of evolving processes and systems where full reconciliation was never achieved. He added that these discrepancies create “lost time, reduced service quality, and obstacles to fault restoration.”
For Janz, the Catalyst is significant because it demonstrates how intelligent inventory reconciliation can unlock the digital twin capabilities needed for intent-driven autonomous networks, while translating into societal and business value through use cases such as autonomous network resilience in natural disasters and proactive service evolution for banks with agentic AI.
José Garcia, Enterprise Architecture Specialist at Entel, said the Catalyst is a strategic priority because accurate, high-quality inventory is essential to the company’s journey toward autonomous networks. He highlighted three direct benefits: modernizing inventory to improve operational efficiency, using disaster simulations to strengthen emergency response and help safeguard lives, and improving B2B agility by accelerating the delivery and accuracy of new enterprise services. “Accurate data isn’t just a technical requirement - it is a life-saving asset and a driver of significant business value,” he said.
At DTW Ignite 2026, Agentic network resilience and lead to quote using AI-driven digital twin showcased real-time inventory reconciliation and digital twin simulations. The demonstration highlighted how operators can predict issues, simulate scenarios and make informed decisions based on accurate network data.
