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

Predictive Intelligence for Optimized Networks & Enhanced Experience Resilience (PIONEER)

Today’s telecom operators are expected to deliver consistent and reliable network experience to consumer and enterprise customers. Managing such a complex network requires high fault tolerance measured on its number of 9’s availability and shorter mean time to restore. We understand that the autonomous networks initiative is the key to driving operational excellence by embedding AI, Digital Twins, and intelligent Agents across network domains. Yet, one of the biggest challenges for nearly all operators lies within their own assets: data. Data is the critical fuel for autonomous networks—but today, most operators face significant hurdles: * Siloed Data Sources – Disparate systems create inconsistent and fragmented data, undermining the foundation of automation. * Lack of Data Governance – Without centralized control, data quality, security, and compliance risks multiply, eroding trust and slowing transformation. * Inefficient Data Processing – Inconsistent and incomplete data delays reporting and decision-making, ultimately stalling self-optimizing networks. Our approach breaks down silos and federates telecom inventory data using AI and TM Forum-defined standards (ODA, Canvas, OpenAPI, DT4DI). This unified data fabric enables CSPs to: Enhance network resilience with predictive AI use cases, such as: * AI Copilot for complex network operations, enabling automated troubleshooting and planning * Real-time inventory visibility across physical, virtual, and logical assets—spanning IT, RAN, edge, and AI-driven data centers Democratize data access by extending unifying inventory management, PM, FM allowing CSPs to govern and scale AI-driven insights organization-wide To overcome this fragmentation and move toward autonomy, the PIONEER Catalyst—led by Globe, in partnership with Singtel Group, Dell Technologies, FNT, and NVIDIA—embraces the A-B-C-D framework to align with TM Forum’s Autonomous Networks vision. As a key OpCo of the Singtel Group, Globe is leading the Group-wide Autonomous Networks (AN) program launched in 2023 — serving as the AN Practice Coach and proving ground for strategic innovation and scalable execution. Following TM Forum’s IG1326 blueprint, Globe is driving the development and validation of high-impact L3 and L3+ use cases across operations, with other OpCos set to adopt and scale these learnings. Innovation & Differentiation * End-to-End AI-Driven Telecom Stack – Integrates GenAI, geospatial network views, and predictive analytics for a smarter, self-optimizing network * Open and Standards-Based Architecture – Built on TM Forum best practices to ensure interoperability and future scalability * AI-Powered Network Inventory Management – Automates resource tracking and optimizes capacity utilization in real time

URN: C25.0.852

Project details

AI-powered ODA in a Box for B2B2X

Telecom companies are increasingly adopting AI-driven composable software to enhance BSS/OSS agility, AI-powered operations, and scalability. The market for composable software ecosystems is growing rapidly as businesses seek more flexible, scalable, and modular solutions. Composable platforms allow companies to build applications using interchangeable components with Open APIs, making it easier to adapt to changing business needs. In response to this need, TM Forum created the Open Digital Architecture (ODA) building a suite of ODA components which perform BSS and OSS functions. The next step from ODA components is to deliver a fully defined “ODA in a Box.” ODA In a Box is a modular, deployable package that embodies one or more pre-integrated ODA Components, designed according to TM Forum's LEGO-wise architecture principles. It provides a cohesive, self-contained unit of functionality that is: * Composable: Built as a "LEGO block" in the ODA architecture, enabling plug-and-play integration with other ODA components. * Pre-integrated: it aggregates multiple ODA components where needed, manages interdependencies internally, and ensures the external interface remains clean and compliant. * Canvas-ready: Deployable on a reference ODA Canvas (cloud-native environment), supporting lifecycle management and orchestration. * API-driven: It exposes all its capabilities through TMF Open APIs, ensuring interoperability and automation. * Encapsulated Complexity: Any internal dependency among included components is abstracted from the rest of the system, enabling a simplified and consistent external behavior. AI-powered ODA in a Box for B2B2X Catalyst delivers multiple use cases to depict the usage of ODA components that enable an operator to quickly deploy an AI-powered capability. Each use case integrates in “boxes” from multiple vendors to enable a B2B2X solution. For example, a cloud connectivity service at the edge delivered by a CSP includes a partner supplied cloud capability and is sold to an enterprise. UC 1 – Lead to Order (Pre-Sales & Sales Process) In the B2B2X market, sales leads emerge and vanish rapidly, making them difficult to capture. The sales team needs an efficient way to capture and track these leads. The conversion rates from lead to opportunity and from opportunity to order are low. When the SLA enterprise order fulfillment does not meet customer expectations, we need to find another solution for the pre-sales and sales processes. ODA in a Box facilitates the creation of AI copilot/agent-driven pre-sales and sales processes, expediting order implementation and integration. Our goal is to show that pre-sales is enhanced by implementing a Gen AI copilot/agent within the ODA Boxes. Utilizing the B2B sales knowledge from the telco sales team, the RAG is updated through a knowledge management component and the recommendation management component to enhance the lead to opportunity to quote process enabling the appropriate solution recommendation for quick order creation utilizing product catalog component, product order caption component, and product order delivery and orchestration components. Each ODA in a Box communicates via the TMF Open APIs to conclude the process of orchestration and inventory management. AI-driven operations and recommendations leads to a higher sales conversion rate. Revenue growth is achieved through the optimization of pre-sales, sales, and post-sales activities. Costs are reduced through agile integration within the boxes and improved coordination between them. Time to market is decreased thanks to pre-defined and tested boxes. UC 2 – Idea to Cash The process of preparing a new product offering is time-consuming and requires considerable CSP product management effort. Designing offers that meet market demand is always a challenge. Time to market for new offers doesn't usually meet marketing expectations. This use case utilizes an AI-driven offering design delivered through an integrated ODA in a box solution. The LLM-based AI copilot for intelligent B2B offering design contains three functions delivered by ODA components as follows: * Offering knowledge using “TMF060 Knowledge Mgmt.” * Offering proposal using “TMFC050 Recommendation Mgmt.” * Offering market performance prediction using “TMFC058 Product/Sales Performance Mgmt.” This ODA in a Box is then combined with another vendor’s ODA in a Box with product configuration and catalog management to enable idea to cash. The value of this B2B2X solution is improved accuracy of the new offerings for the specific niche market or the target customer. We are allowing “easy-to-do” offering design and testing and reduces the time to market for new offering releases. What does this mean for DTW Copenhagen? For DTW, this project built working demonstration of ODA-in-a-Box — utilizing the ODA architecture, designed for faster deployment, ease of scalability, and newly AI-powered. By leveraging macro components, CSPs will be able to adapt quickly to new technologies and growing connectivity demands. Please come see us in the Moonshot Catalyst area at DTW!

URN: M25.0.779

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

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

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

End-to-end service realization using intent-based networks

CSPs have long been faced with an unforgiving trilemma. When building and operating commercial networks, you can optimize for any two of three critical factors: scale, reliability and efficiency – but never all three simultaneously. As market demands and customer expectations make scale and reliability non-negotiable requirements, CSPs are forced to sacrifice efficiency. This compromise translates into high operational costs and low profit margins, exacerbated by intense competitive pressures. To address this challenge, CSPs need to fundamentally transform how they manage the lifecycle of their networks, by shifting from a task-based automation paradigm to intent-based autonomy, where every aspect of network lifecycle - from initial planning and deployment through ongoing operations to eventual decommissioning - is driven by business intents and a knowledge plane. To that end, this Catalyst is demonstrating the practical implementation of TM Forum Open APIs and intent-based management across multiple layers - from business objectives through service management to the deployment of rApps (software that helps optimize network traffic). The goal is to build a self-adaptive system that will reduce CSPs’ costs through greater automation. The project combines the TM Forum Autonomous Networks Reference Architecture, including autonomous domains and intent management functions, with ORAN (open radio access network) interfaces, such as R1 and SMO services. Aiming to demonstrate the technical feasibility of theses APIs and models, the Catalyst will identify and close any gaps. The project team notes the importance of integrating the TM Forum-based management with modern network management architectures, such as ORAN SMO, which provides an open and flexible environment.

+11

URN: M25.0.799

Project details

InfraVerse: Breaking boundaries for XR sustainability

Telecom infrastructure deployment—especially for rooftop, in-building, and dense urban environments—remains slow, costly, and error-prone. Existing planning methods rely on static blueprints, fragmented site data, and repeated site visits, leading to rework, delays, and missed revenue opportunities. The InfraVerse Catalyst addresses this bottleneck by applying telecom-specific building information modelling (BIM) to digitize the physical deployment process. It integrates drone imagery, AI-driven insight extraction, and genAI automation to transform how CSPs plan, validate, and deploy high-performance infrastructure—particularly in hard-to-serve, high-value areas. The Catalyst combines drone-based data collection, AI, and generative AI (genAI) with a telecom-specific BIM platform. Drones capture detailed visual data. AI then processes this data to extract structural, spatial, and environmental insights. Next, genAI generates critical documents—like EMF assessments, technical drawings, and permit applications—reducing manual work and speeding up compliance. This solution allows virtual site inspections, improves design accuracy, and reduces unnecessary travel. Teams collaborate more effectively using a unified digital model, streamlining deployment and cutting costs. CSPs can plan with greater precision, optimize equipment placement, and deliver stronger indoor and outdoor coverage. The system is scalable and sustainable - it enables energy-efficient design, lowers emissions, and helps meet green building standards. With fewer design errors and faster approvals, CSPs can deploy infrastructure faster, at lower cost, and with better quality control. The InfraVerse Catalyst helps CSPs break free from slow, reactive builds—replacing outdated planning with intelligent, digital-first workflows. The shift brings sharper accuracy, faster deployments, lower costs, and sustainability gains that can’t be ignored. It’s not just better planning—it’s a smarter path to market and a stronger, greener foundation for the networks of tomorrow.

URN: C25.0.802

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

Growing B2B with autonomous agents

CSPs worldwide are looking to B2B as the driver of growth, enabling them to capture new revenue by supporting the digital transformations of business customers. But serving the midmarket – where the largest number of customers can be found – is a challenge. This situation only becomes more of a challenge as CSPs look to grow their presence in the B2B space, monetizing advanced network capabilities and bundling partner products and services in order to create tailored solutions for enterprises. The answer to this comes through a generative-AI enhanced lead-to-care process to pivot from a human-agent driven engagement to a customer led journey empowered by Generative AI. GAI agents will enable customers to find relevant products using semantic search, creating customized solutions that meet their specific business requirements, budgets and timelines. We are creating a scalable platform that not only streamlines deployment but also provides a flexible base for future enhancements through integration of additional components and capabilities, built to align with the ODA in a Box principle. The catalyst also leverages Model Context Protocol (MCP) as a common communication mechanism between both ODA canvas and AI agents, providing a future-ready, modular, telco-grade foundation for the agentic solution. Unlock profitable growth from the B2B midmarket * Faster time to implement Faster to deploy, scale and enhance through support for the ODA in a Box approach * Improved customer satisfaction Give midmarket B2B buyers a customer driven, agile and flexible commerce experience * Increased deal capacity Using genAI and automation to profitably serve more customers

URN: M25.0.797

Project details

Messy data in, treasure out: boosting Autonomous Networks

To build an autonomous network that will increase customer satisfaction and reduce costs, CSPs need to be able to accurately manage the network status. One important requirement is network configuration information. However, many CSPs track network configurations using multiple methods, and the data is siloed and not standardized. These issues, which also impact IT systems, are particularly prevalent in legacy networks. To solve this problem, this Catalyst is using AI to collect a wide variety of configuration information and process it into data formats which will enable CSPs to visualize and manage network configurations. The standardized data is also provided to the network inventory management function, which can then optimize network configurations. The ultimate goals are to enable the network to heal itself, in the event of a fault, and allow CSPs to make intent-based changes to the network configuration management. By employing AI to process and format data, CSPs don’t need to conduct manual data analysis, processing, and formatting – thereby paving the way for more autonomous networks. Furthermore, end-to-end network configuration management will improve customer satisfaction, reduce support costs, streamline operations and improve CSPs’ return on investment.

URN: C25.0.830

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

Digital Twin acceleration: Automate ODA Framework adoption using enterprise architecture tools

Enterprise architecture tools can help to unlock the value of the TM Forum’s Open Digital Architecture (ODA). But CSPs need straightforward ways to import certain functional blocks and components from the ODA catalogue into an EAM enterprise asset management (EAM) tool. This can be a time-consuming task involving manual interpretation of documents and creation of components in the EAM tool or the conversion of files into intermediary formats compatible with the EAM. The first phase of this Catalyst is harnessing APIs and AI to automate the import of functional ODA blocks and components. Using APIs enables CSPs to include more density in their models, allowing for cross-framework relations, for example. By eliminating the need for engineers to craft integration mechanisms themselves, the solution will remove a key obstacle to widespread adoption of ODA. This will help CSPs benefit from a vast amount of industry-created assets, ranging from the business process framework, through the framework and design principles of ODA, to the specifications for standardized plug and play software of components, canvas and open APIs. For CSPs, the net result should be faster deployment and adoption, fewer work hours required, more consistency in modelling and a base for high quality AI-inference. The output of the Catalyst should also make it easier for B2B2X partners to work with CSPs. “As a TM Forum active member, we get significant value from being able to automatically import the TMF reference frameworks, their inter-relations and to keep them updated as they evolve,” says a Project Champion at NOS. “We believe this can dramatically improve de facto member adoption, benefitting the whole ecosystem.” To assess its impact, the Catalyst will monitor the ability of the solution to create an object space that enables CSPs to perform enterprise architecture activities and develop reports, and support advanced use cases, such as AI-based querying. From a TM Forum standpoint, a key metric will be the number of successful framework integrations by members.

+10

URN: C25.0.781

Project details

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