2024 Catalyst Projects

See Innovation Come To Life

At the heart of innovation at Innovate Asia, 10+ Catalyst projects will debut their groundbreaking innovations live in the expo hall and on the Innovate stage.

Harnessing the collaborative global force of the greatest industry minds from global organizations, our Catalyst project teams are pioneering solutions to propel industry innovation and growth through Open APIs, ODA, AI, and automation.

Experience first-hand their inventive and trailblazing demonstrations. Delve into the challenges tackled, use cases explored, and solutions forged. Connect with these visionaries to discover how you can leverage their achievements to align with your business objectives and advance future outcomes.

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Browse Catalyst Projects

Zero network outages using resilient automation

Major network accidents can result in huge economic losses and have a serious brand impact for CSPs. Such incidents can arise from network architecture corruption, increasing network scale and complexity and APT (advanced persistence threat) attacks. Failures in network security and resilience can lead to regulatory compliance issues, as well as serious business continuity issues, data breaches and millions of dollars in losses. Leveraging advanced technologies, such as AI and digital twins, this Catalyst is developing a comprehensive tool platform to enhance network resilience and address disruptions for operators. The solution comprises two key components. The first component focuses on mitigating risks in network architecture. To identify vulnerabilities, it supports network blueprinting, simulation, analysis and optimization, enabling quick recovery and enhancing network performance. The second component focuses on risks related to network changes. Prior to implementation of the changes, the platform performs configuration verification, simulation and a deployment comparison to prevent disruptions. As the tool platform identifies network risks and configuration faults, operators can optimize the network, according to its suggestions, and reduce the number and impact of network incidents. In the event of a power failure, for example, the operator could switch all services to a redundant path, potentially preventing a prolonged outage that would affect million users. As well as boosting network resilience, the proposed platform should improve operational efficiency and security, ultimately enhancing brand reputation. CSPs AIS and HKT, which are Project Champions of the Catalyst, plan to use the platform to help build level four autonomous networks that are highly resilient and further their business development.

URN: C25.0.773

Project details

NeuroNOC: The self-healing network brain

CSPs face multiple challenges in network operations. These include long delays in diagnosing the root cause of faults and identifying the right solutions, making and rectifying unnecessary changes in the network, and an inability to be proactive in assurance. The net effect can be poor customer experience and inefficient operations. This Catalyst is developing a solution that combines and correlates all the relevant data in a common data layer to immediately identify the root causes of faults and potential solutions, and support intent-based service assurance. The common data fabric will aggregate data from alarms, performance, configs, topology, logs and results through a single pane of glass, using both predictive and generative AI to learn with minimal input from network experts. The solution can then recommend accurate, immediate, detailed and automated resolutions to network issues. The Catalyst is employing TM Forum best practices, including the Open Data Architecture and APIs. The team will directly measure the impact of the project by tracking how the resulting solution reduces costs and effort in level 1, 2 and 3 operations. The solution should also reduce the wastage resulting from incorrect or unnecessary changes to the network, time spent on service operating manuals and the poor performance of the network due to incorrect or sub-optimal configurations.

URN: C25.0.814

Project details

AI-powered end-to-end solution for customer experience

According to McKinsey, contribution of network experience for customers choosing their network provider or churning is close to 20%. Advancements in AI empower telecom operators to better understand individual customers' network experiences, enabling ROI-maximizing capital allocation and improved reliability. The challenge lies in comprehending usage patterns and connectivity performance from the end-user's perspective, all while optimizing network quality and customer satisfaction within the economic constraints faced by CSPs. To address this challenge, we will collect anonymously real customer connectivity insights 24/7 from end-user devices. To address privacy concerns, we introduce DePIN mechanism, which gives reward for end users. Our data collection methodology is the most sustainable way to collect network performance and quality data tied to real customer experience. It is lightweight and has a very marginal impact on users’ data plan and on the radio access network in terms of added traffic load and energy consumption. Collected insights are correlated with network-based data from access networks, transport layers, and core infrastructure to create an end-to-end holistic view of service delivery. Typical cases include strategic investment planning, proactive quality improvements, cloud diagnostics, and accelerated customer complaint resolution. The AI/ML-powered system automatically identifies performance bottlenecks, detects emerging trends, prioritizes issues based on customer impact severity and makes recommendations. To assure maximum accuracy and extreme automation we applied Digital Twin artefact contributing toward Autonomous Networks Level 4 and for cases where human decision is needed, we provide intuitive GUI utilizing latest XR technology. By addressing connectivity issues proactively rather than reactively and shifting focus from network metrics to customer perception, CSPs can reduce churn, enhance customer satisfaction, and optimize network resources based on real-world usage patterns rather than theoretical models. Let’s bring the customer back into the centre of the CSP decision making by addressing proactively their connectivity issues!

URN: C25.0.845

Project details

Beyond Chatbots: Hybrid AI for fully automated proactive customer care - Phase II

Only 1 in 25 Unhappy Customers Will Complain The other 96% remain silent—leaving service providers with a costly blind spot. This silence leads to unresolved issues, missed opportunities for intervention, and ultimately, silent churn. For telecom operators, this means not just lost revenue but a failure to meet customer expectations. The Problem with Traditional Care Legacy care systems are reactive. They rely on customers to initiate the support journey—by calling, clicking, or complaining. Even with chatbots, dashboards, and predictive models in place, most tools operate in silos. They detect technical issues but rarely connect those issues to the specific customers affected, leaving care teams without the clarity or speed needed to respond effectively. The Shift to Proactive, Autonomous Care Phase One: Assisted Care In the beginning, AI played a supporting role in reactive care. Once a customer initiated contact—through a call, chat, or complaint—AI stepped in to predict intent, route queries, and prioritize responses. It helped optimize workflows, but only after the problem had surfaced. Phase Two: Autonomous, Proactive Engagement Now, we’ve flipped the model. When a service issue is detected in real time, the system identifies which customers have been affected. It then predicts how those customers are likely to respond—whether by calling support, submitting a complaint, or silently churning. Based on this prediction, the system proactively engages with each customer to address the issue before they take action. This Catalyst transforms telecom care from reactive support to proactive, intelligent engagement—delivered through a robust Hybrid AI approach built to scale across millions of interactions. AI at the Core of the Solution Built for telco, Designed for scale. * AI at the core – The operational engine, not a bolt-on * Closed-loop automation – From detection to resolution, no handoffs * Silo-breaking integration * ODA-aligned – Modular, open, and fast to deploy Business Impact Even in pilots delivered : * 30%+ improvement in service quality * 80%+ satisfaction in AI-led interactions * Reduced call volumes and churn * Increased upsell/cross-sell * Lower operational costs through automation The Result: Productivity at the core. Scale at the edge. Satisfaction across the journey.

URN: C25.0.767

Project details

Broadband as a Service: The future of wholesale broadband ordering – Phase II

With the rising demand for fast and reliable connectivity, there is a growing need for standardized frameworks to enable efficient and rapid deployment of broadband services. Today, disparate standards for fiber networks and mixed implementations result in delayed deliveries and high costs for service providers. The standardization of APIs in the fiber wholesale ecosystem would deliver interoperability, scalability and simplicity for service providers and network operators alike. To that end, this Catalyst aims to provide a unified API framework to support seamless integration between wholesale fiber providers and retail service providers, regardless of geographic location or technology stack. Building on Phase I, which developed a draft and basic implementation, Phase II of the Catalyst will deliver a working standard which is available on the TM Forum website and consists of an API profile, Open API definition, user documentation and CTK (compliance toolkit). The proposal, which will leverage the latest versions of the TM Forum APIs, will help enable zero-touch automation between access and service providers. It will also lay the foundations for further extension into service provider products to build a common framework for the broadband ecosystem. By standardizing these APIs, the industry can reduce complexities related to vendor compatibility, streamline onboarding processes and facilitate faster delivery of fiber-based services. Standardization will also reduce implementation costs, while still allowing individual vendors to customize for their own individual regional and commercial requirements. In future, the project could be extended to service providers offering products to end users, helping build an ecosystem based on common definitions that further simplify and reduce IT costs.

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URN: C25.0.811

Project details

AI-driven sustainable connectivity: Cutting emissions for higher impact

CSPs are expanding their digital infrastructure—and as they do, energy consumption continues to rise. This increases both operational costs and carbon emissions. This Catalyst addresses the urgent need to optimize energy use across network operations using AI, machine learning, and data analytics. The solution integrates an AI-driven analytics engine into the network management layer. It ingests telemetry data from power systems, equipment performance logs, and traffic patterns across both access and core domains. Using machine learning models, it detects anomalous energy use, forecasts load requirements, and dynamically adjusts network parameters—such as power modes, cooling profiles, and traffic routing—to minimize unnecessary consumption. These adjustments occur in near-real time, reducing operational overhead and extending the usable life of hardware. The solution follows TM Forum Open Digital Architecture (ODA) and Open APIs for modularity and interoperability. As a result, it supports modular deployment and seamless integration with existing OSS/BSS systems. Unlike traditional methods, this solution combines predictive analytics with intent-based automation. It supports smarter energy provisioning for both access and transport networks—reducing over-provisioning and unnecessary energy draw. CSPs gain a clearer view of their carbon footprint and can align energy-saving initiatives with broader sustainability targets. The business value is twofold: reduced energy and maintenance costs, and improved brand reputation through demonstrable sustainability leadership. In a market where environmental accountability increasingly influences customer and investor decisions, this Catalyst enables CSPs to lead by example. By embedding intelligent energy optimisation directly into operational workflows, CSPs can cut emissions, boost uptime, and reduce costs. Crucially, this Catalyst will demonstrate that they can do this without compromising performance. The aim is to show that sustainability isn’t just good governance—it’s a core driver of resilience and long-term growth.

URN: C25.0.770

Project details

AN L4 Digital Twin ensures maximum service reliability

Service is revenue. Better service is better revenue. Reliable service is reliable revenue. High service reliability has always been the key to success for CSPs and the telco industry as a whole, yet even minor configuration errors can trigger network-wide failures, causing severe revenue losses. IP network failures often escalate to core service outages, while massive-scale device connections exacerbate operational complexity. Statistics reveal that 70% of global IP incidents stem from human configuration errors, exemplified by an operator making 6,000 annual manual changes with 10+ human-induced errors and outages yearly. Exponential growth in CSP network complexity drives hundreds of annual configuration changes, with single IP devices handling ~600K configuration lines. Manual analysis remains prevalent, causing inefficiency, human dependency, and most importantly it simply cannot fully mitigate the risks. Therefore, relying on human intervention is destined to become obsolete. With our solution, CSPs can pre-emptively identify misconfigurations and service impacts, eliminate human-induced network failures, have a much faster network change process, reduce reliance on 5+ year-experienced O&M staff. This alleviates executive concerns about network change accidents which has been a long-standing issue. Zero-Accident Guarantee: Pre-emptive identification of misconfigurations and service impacts, reducing network change risks. Intelligent Verification: Automated network-wide analysis of routing and traffic changes, replacing error-prone manual checks. Real-Time Emulation: A digital twin mirroring live networks to test changes virtually, eliminating the need for multi-day physical monitoring. Operational Efficiency: Accelerated testing/troubleshooting and reduced resource costs via lightweight, high-precision simulation. By shifting from reactive to proactive operations, this solution empowers CSPs to execute network changes confidently while safeguarding service continuity.

URN: C25.0.828

Project details

Agentic ODA for proactive customer experiences

Imagine a world where telecom services don’t wait for problems—they anticipate them. Where AI-powered agents within ODA components communicate not just with customers, but with each other—across systems, channels, and business domains, autonomously. No more call centers stuck in reactive loops. No more fragmented support journeys. This is our moonshot: a proactive, modular, AI-driven telecom experience built on TM Forum’s Open Digital Architecture (ODA), powered by Agentic AI. The Problem We’re Solving Today’s telecom support is passive and reactive. Whether it’s a billing error, service disruption, or plan query, the customer must initiate contact—typically navigating complex IVRs, chatbots, or long wait times. Issues are ticketed and routed through siloed departments. Even with current AI tools, agents remain standalone—confined to narrow domains and unable to collaborate across systems. The result? Slow resolutions, frustrated customers, high operational costs, and limited scalability. Every new product or service often requires staff retraining, custom integrations, and lengthy setup cycles—driving up both cost and time to market. Our Vision We envision a telecom experience led by a Concierge AI Agent—a proactive, intelligent assistant that continuously monitors the customer journey and engages before problems arise. And it doesn’t work alone. It’s supported by an AI ecosystem in which ODA components communicate via open APIs and natural language protocols. This is Agentic AI: autonomous, collaborative, and interoperable. Building on the ODA-in-a-Box concept, our architecture enables AI agents to discover each other, orchestrate actions, and respond to customer needs instantly—without manual handoffs or redundant data collection. How It Works When a service issue or anomaly occurs, the Concierge AI is alerted. It gathers context from billing, network, and service systems, consulting with other AI agents in real time. It then reaches out to the customer with personalized insights and solutions—before they even ask for help. But it doesn’t stop at problem-solving. The agent offers concierge-style services: tailored plan suggestions, proactive updates, and loyalty offers—drawing on cross-domain intelligence. The result is a seamless, responsive, and deeply personalized customer experience. Our Goals Our goal is to enhance ODA standards to support AI-to-AI interoperability. We’re introducing intelligent orchestrator components that enable proactive service management—shifting telecom operations from reactive containment to predictive care. We're also proposing API enhancements to support natural language discovery and communication between agents embedded within ODA components. The Impact This architecture will accelerate operational delivery while transforming both support costs and customer experience. By eliminating complex integrations, businesses can launch new operational services over 40% faster. Repetitive tasks vanish. Manual triage disappears. AI agents scale instantly, and operations become leaner. Customers benefit from faster resolutions, proactive engagement, and hyper-personalized experiences. Businesses benefit from improved Net Promoter Scores, reduced churn, and stronger brand loyalty. The Future We’re not just reimagining telecom support—we’re redefining how digital services interact with people. Our Agentic AI-powered ODA framework enables a future where building new anticipatory operational services—like this concierge agent—is cost-efficient, seamless, and swift.

URN: M25.0.793

Project details

BIND: Bridging Intelligence, Networks, and Digital Twin

Executive Summary In a recent benchmark report on Autonomous Networks (AN) involving 111 CSPs, TM Forum asked about the main challenges CSPs face when implement AN. The highest rated was integration across domains. This Catalyst combines the power of data management, AI and telco expertise to demonstrate how Digital Twins and Agentic AI can bridge across data and operational silos, revolutionizing the way networks and services operate. Challenge CSPs are at a crossroads, grappling with profitability challenges in an ever-evolving digital landscape as new technologies and services are introduced. As they seek innovative solutions, one strategy stands out: enhancing network autonomy to boost efficiency, elevate service quality and reduce operational costs. The industry’s vision? A paradigm shift from traditional human-led automation to cutting-edge autonomous networks where systems operate independently (AN Level 4 and above). Technologies such as AI, ML and GenAI are propelling CSPs forward on this transformative journey, but their success depends on bridging across data silos to provide accurate, comprehensive data. Solution Our solution demonstrates how disparate network and service data from inventory and assurance systems can be ingested and stored in a flexible data and AI layer, which is used to proactively identify service impacting issues. Autonomous, GenAI enabled Network Agents address these issues, preempting customers’ complaints by maintaining their service intent. These Network Agents, relying on comprehensive knowledge bases, recommend, simulate and resolve the proactively identified issues. This approach is aligned with TM Forum’s Digital Twin for Digital Intelligence (DT4DI) collaboration and demonstrates how operational efficiency and customer experience can be enhanced by combining Digital Twins and Agentic AI. TM Forum assets This solution uses several TM Forums assets, such as Open APIs (TMF686, TMF639, TMF 642, TMF921, etc.), and guides (IG1307 Digital Twin for Decision Intelligence (DT4DI)). Additionally, it uses Google's recently launched open Agent to Agent (A2A) Protocol, adopted by over 50 organizations, to support agent interoperability. Benefits This solution unlocks numerous benefits for CSPs, their customers and society. * Enhanced service quality and customer experience * Increased autonomy, efficiency and cost savings in operations * Superior reliability for emergency services and the digitalization of society “Innovating to cut operational costs and improve network service quality is essential. Utilizing Digital Twin and Agentic AI technologies to integrate existing fragmented data, we aim to establish autonomous processes capable of proactively identifying and resolving network issues,” explains one of the Project Champions at Vodafone. “This approach is designed to preemptively address potential network problems, thereby preventing any service impact.”

URN: C25.0.775

Project details

AN agent for 5G bearer networks

The 5G bearer network, which connects the 5G radio access network and the core network and supports high quality private line services, plays an extremely important role. But troubleshooting on the bearer network can be difficult. On one hand, alarms and faults frequently occur. For example, a broken optical cable broken may trigger hundreds of device alarms. On the other hand, it typically takes several hours for experts to complete a fault diagnosis and the on-site engineer often needs to contact the network operations center to obtain support. Yet during typhoons and other disasters, emergency relief and communication recovery must be completed quickly. This Catalyst is creating an intelligent fault management framework, encompassing network devices, the network management system (NMS) and the operations support system (OSS). The framework employs AI agents to automate the monitoring and diagnosis of root alarms, in place of manual operations, in common fault scenarios. In a scenario where a fault needs to be manually diagnosed, an AI copilot will provide support to the engineers via a natural language interface. A major step towards the development of a level four autonomous network, the end-to-end solution is based on a three-layer architecture that associates digital twins with AI foundation models. Drawing on embedded AI, the intelligent network element (NE) layer provides real-time awareness of the network status. The intelligent NMS layer enables self-closed-loop fault diagnosis in a single domain. Integrated with the NMS, the intelligent OSS layer can address fault scenarios across domains and vendors end-to-end. Having completed technical pre-research, the solution is being piloted by China Mobile Guangdong. After it is integrated into production, operations and maintenance in the province, the solution should greatly improve network stability and reliability, by reducing the time it takes to resolve faults. Improved data query efficiency and a more robust emergency response capability for natural disasters are also expected.

URN: C25.0.848

Project details

CX optimization via AI-driven SOC over autonomous networks

This Catalyst – championed by Claro Colombia, Claro Brasil, and Libyana Mobile – showcases how an AI-powered SOC can predict issues before customers notice, automatically resolve incidents, and align network performance with customer expectations. Built on TM Forum Open APIs, the architecture enables seamless interoperability, fast integration in brownfield environments, and real-time automation. It delivers a replicable framework – a modular, standards-based blueprint adaptable across operations, domains, and technologies. Designed for scalability, it accelerates autonomy through proven patterns and automation models. Why It Matters Telecom networks are more complex than ever, yet customers demand flawless connectivity and fast resolutions. Traditional NOCs fall short of managing customer experience. Frameworks like TM Forum’s Open APIs, Closed-Loop Automation, and MAMA highlight the need for integrated, real-time, customer-focused operations. A customer-centric SOC is key to resolving issues before they impact users, improving satisfaction, and reducing costs and churn. How It Works The SOC collects data from all layers of the network — access, transport, and core — and consolidates it through a cross-domain Data Mediation Layer capable of handling diverse protocols and systems. This enables a unified operational picture built from alarms, KPIs, logs, and real-time performance. But observability alone is not enough. The SOC enhances this picture with customer-centric signals — such as QoE, crowdsourced metrics, complaints, and churn risk — to understand not just what’s broken, but how it impacts the customer experience and the business. An AI/ML engine detects anomalies and predicts service degradations. When issues arise, an intent-based automation engine maps them to appropriate actions using TM Forum Open APIs, closing the loop with continuous validation. Key Benefits * Proactive Customer Assurance: Identify and resolve service issues before users experience them. By focusing on QoE and customer context, the SOC elevates satisfaction and reduces inbound complaints. * Faster Time to Resolution: Intent-based automation enables rapid remediation, decreasing MTTR and ensuring consistent service availability. * Reduced Churn Risk: With real-time insight into customer impact and contextual business signals, high-value accounts are protected from persistent quality issues. * Operational Efficiency: Automation handles routine tasks, allowing SOC teams to focus on strategy and innovation. The unified view improves collaboration across digital operations, network, and customer-facing teams. * Scalable, Reusable Architecture: Built on TM Forum Open APIs and aligned with the ODA and MAMA frameworks, the solution provides a blueprint for autonomous operations that can be replicated across CSPs. Expected Outcomes * Decrease in customer-initiated trouble tickets and care center interactions. * Improved perceived reliability, especially in high-ARPU segments. * Increased Net Promoter Scores as customer disruptions become rare and short-lived. * Lower operational costs through intelligent automation. * Industry-aligned reference architecture, validated by TM Forum's Value Operations Framework (VOF), and designed to accelerate autonomy adoption across telecom environments.

URN: C25.0.806

Project details

Agent Fabric - Phase II

Modern Network Operations Centers (NOCs) are under pressure—grappling with manual processes, delayed fault detection, rising incident volumes, and challenges in rapid service restoration. Where automation exists, it is only in fragments. Some teams rely on custom scripts, others on domain-specific AI tools. This patchwork of solutions leads to inefficiency, inconsistency, and missed opportunities for scale. The Agent Fabric Catalyst tackles these issues head-on by enabling a collaborative, multi-vendor ecosystem of autonomous agents designed to operate across different network domains. Instead of isolated scripts or siloed intelligence, it orchestrates specialized agents that work together across network domains. Building on the Phase 1 Incident Copilot, which automated single-domain fault handling, Agent Fabric now extends to cross-domain, allowing specialized agents to autonomously detect, diagnose, and resolve across RAN, transport, and core domains. What Agent Fabric Delivers: * Reduced Manual Effort: Agents automate repetitive and error-prone NOC tasks, improving operational speed and consistency. * Faster Incident Resolution: With intelligent detection and cross-agent coordination, issues are addressed more quickly. * Multi-Domain Execution: Agents operate across previously siloed systems, reducing the need for complex integrations. * Modular & Scalable: Agents can be added or upgraded independently, avoiding disruption and supporting incremental adoption. The Agent Fabric provides a production-ready Agent Registry, supports seamless agent discovery, and enables a plug-and-play model for introducing new capabilities—without requiring a full overhaul of existing systems. Whether it’s identifying root causes, accelerating ticket resolution, or enabling service optimization, Agent Fabric shows how telcos can scale autonomy and boost efficiency—one agent, one domain at a time. Agent Fabric turns fragmented automation into layered yet endogenous intelligence. Instead of siloed scripts or isolated AI tools, it connects autonomous agents across the business, service, and resource operational layers— aligning with TM Forum’s AN L4 Target Architecture. The result: scalable, closed-loop autonomy that evolves network operations without disrupting them.

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URN: C25.0.798

Project details

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