2025 Catalyst Projects

See innovation come to life

At the heart of innovation at Innovate Asia, 15+ 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 will demonstrate their proof-of-concept solutions. Connect with these visionaries to discover how you can leverage their achievements to align with your business objectives and advance future outcomes.

Make sure to add these Catalysts sessions to your agenda:

25 November | 12:30 PM - 1:20 PM: Catalyst Spotlight: Shaping the Future of Autonomous Networks
25 November | 2:30 PM - 3:10 PM: Catalyst Spotlight: Transformation with AI and Data Innovation
25 November | 3:10 PM - 4:00 PM: Catalyst Spotlight: The Power of Composable IT and Ecosystem
26 November | 12:00 PM - 12:40 PM: Catalyst Moonshot Spotlight: AN Level 4 Challenge
26 November | 12:40 PM - 1:10 PM: Catalyst Moonshot Panel: AN Level 4 Challenge

Catalyst Champions include:

Browse Catalyst Projects

ODA monetization engine: Transforming data assets into business growth

Introduction – ODA Monetization Engine Catalyst In an era where data is the new currency, communication service providers (CSPs) and enterprise verticals face mounting pressure to unlock the full value of their data assets. Despite generating vast volumes of operational, customer, and network data, most organizations struggle to monetize it effectively. Legacy systems, siloed architectures, and manual processes prevent real-time insight generation and hinder the adoption of advanced technologies like AI and digital twins. The ODA Monetization Engine Catalyst addresses this challenge by delivering a transformative platform built on TM Forum’s Open Digital Architecture (ODA). It enables CSPs and enterprises to transition from static data handlers to dynamic digital service orchestrators—unlocking new revenue streams, enabling autonomous operations, and accelerating innovation. The Problem Most CSPs operate in fragmented environments where data is disconnected from monetization opportunities. This results in: * Delayed time-to-market for new services * Limited ability to personalize offerings * Underutilization of AI and digital twin capabilities * Missed opportunities for partner-driven growth The Solution The ODA Monetization Engine is a modular, scalable platform that integrates: * Real-time data ingestion and enrichment to convert raw data into actionable insights * Analytics-as-a-Service for predictive intelligence across customer, network, and service domains * Decision Intelligence to dynamically segment users based on behavior and value potential * Partner-ready API exposure using TM Forum Open APIs for seamless integration * Flexible billing models supporting usage-based pricing, dynamic bundling, and real-time charging Impact This solution is not theoretical—it’s validated in production. Telkomsel, Indonesia’s leading mobile operator, deployed the ODA Monetization Engine and achieved: * A noticeable reduction in service launch cycles, enabling faster time-to-market * Significant new revenue generated from data-driven services and partner integrations * Steady monthly growth from API-based monetization and ecosystem expansion These results demonstrate how the Catalyst delivers real business value—transforming operations, accelerating innovation, and unlocking new monetization opportunities. Industry-Wide Applicability The platform extends beyond telecom, delivering value across verticals: * Governance & Public Sector: Smart city monetization, tourism optimization * Healthcare & Life Sciences: Predictive care models and insurance innovation * Transportation & Logistics: Autonomous supply chain monetization * Finance & Banking: Fraud detection and risk management * Retail & Commerce: Personalized marketing and customer engagement Why It’s a Breakthrough * First ODA-native monetization layer bridging architecture and business outcomes * Embeds AI-driven monetization directly into ODA components * Aligns with TM Forum’s Level-4 Autonomous Operations maturity * Proven at scale: managing 170M+ subscriber data streams By adopting this Catalyst, CSPs and enterprises gain a turnkey solution to transform data into growth—delivering measurable business impact, ecosystem expansion, and future-ready innovation.

URN: C25.5.866

Project details

OmniBOSS - Phase II

OmniBOSS Phase II proves that even with minimal effort, agentic AI can provide contextual insights from real operational data, closing the gap between practice and execution while preserving telecom expertise for the future. OmniBOSS is an Agentic AI platform that revolutionizes how Communication Service Providers (CSPs) operate their B/OSS environments by embedding domain knowledge, best practices, and AI-driven oversight directly into operational workflows. Unlike traditional systems that passively store configurations and metrics, OmniBOSS proactively monitors, evaluates, and recommends corrective actions across B/OSS layers — acting as a real-time expert assistant. In Phase I, OmniBOSS demonstrated a working prototype of Agentic AI for B/OSS best practices using simulated data. The goal was to prove the conceptual feasibility: AI agents can understand, enforce, and recommend operational best practices across TM Forum-aligned domains like alarms, thresholds, and inventory. Phase II builds on this foundation by extending the solution in two key ways: 1. Real-World Data Validation We evolve from simulation to validation against real-world data samples (anonymized or exported from live systems). This elevates credibility by showing how agents respond to actual operational complexity, not just theoretical cases. 2. New Asset – Best Practice Coverage Heatmap We introduce a visual analytics layer that displays which TMF API areas are fully, partially, or not yet covered by best practice enforcement. This new asset acts as a strategic roadmap for CSPs to prioritize improvements and track operational maturity.

URN: C25.5.888

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Agentic framework for unified networks

In a rapidly transforming digital society, multiple access technologies are required to address various needs of business and society, including domains such as maritime, fisheries, oil & gas, manufacturing (IoT), defence, construction etc. In such a transforming environment, consistency, quality of service, time to market, service experience and standards are mission-critical. Today's services and experiences are fragmented, with a tendency to have delays in design, fulfilment and assurance. These need to be resolved for a successful digital transformation of the CSP / Satcom environment. We propose the implementation of a GenAI-powered Agentic Framework to accelerate service innovation and transformation across non-terrestrial networks (NTNs), terrestrial networks and non-telco ecosystems. This solution enables persona-aware, intelligent digital agents that streamline knowledge access, automate strategic decision-making, and reduce time-to-market (TTM) for next-gen SATCOM services. Intelligent agentic ecosystem designed to transform enterprise collaboration and efficiency, features a network of GenAI-powered digital agents enabling cross-silo collaboration, ensure secure role-based access control & enhancing alignment between strategic business goals and technical implementation. Domain-specialized agents trained on TM Forum’s models such as Digital Maturity, ODA, and Open APIs accelerate service innovation, conduct maturity assessments, solutions modelling, and automate repetitive knowledge-driven tasks. Designed for telecom, they are adaptable for cross-industry applications including satellite communications, offering deep intelligence and practical support for digital transformation. The central platform connects these capabilities through a secure and scalable interface supporting intelligent orchestration across enterprise systems. With context-aware automation, teams can effortlessly manage product requirements documentation, define technical architectures, create validation blueprints— enabling E2E service orchestration, faster Go-To-Market & Easy Ecosystem Integration Aligned with TM Forum standards such as Open Digital Architecture (ODA), Digital Maturity Models, and Open API integration, this framework serves as a digital fabric that connects internal teams, external partners, and diverse systems across the value chain.

URN: C25.5.860

Project details

Multi-level multi-agent network fault healing

Communication Service Providers (CSPs) and vertical industries are increasingly demanding automated, intelligent fault management in transport networks. Today, fragmented systems and poor OSS-OMC integration result in manual-heavy, inefficient fault handling processes. As one top CSP leader shared: "We urgently need end-to-end automation in fault management to achieve true service continuity. Manual intervention not only slows down resolution but also increases operational risks." The current challenges — including inaccurate fault identification due to rule-based limitations, slow diagnosis due to reliance on manual tools, and delayed repair due to inefficient communication — severely impact service quality and operational costs. Solving these issues through a multi-layer, cross-domain agent architecture powered by large language models and digital twin technologies will enable accurate fault recognition, rapid root-cause analysis, and secure, automated resolution. This transformation will drastically reduce MTTR (Mean Time to Repair), improve network resilience, and lower dependency on individual expertise, enabling more scalable and intelligent operations. Project Focus: Solving transport network fault handling issues. Traditional methods rely on manual/fixed-rule alarm identification, causing missed/redundant work orders. Cross-domain systems lack coordination; OSS and OMCs don’t interact effectively, hindering automated closed loops, with inefficient manual intervention. Diagnosis takes over 30 minutes (hours for complex faults) via manual/standalone tools, limited by experience transfer. Repairs involve frequent communication or manual operations, with low safety/efficiency. The project uses LLM, Agent tech and small-model algorithms to build a multi-layer cross-domain Multi-Agent system covering network devices. It enables end-to-end automated fault handling via Agent interaction and digital twin simulation. Zhejiang Mobile’s pilot showed 100% alarm coverage, reduced redundant WOs, faster diagnosis, lower costs, and enhanced efficiency. O&M Copilot cuts resolution to 40 minutes, minimizing outages, boosting stability/experience, and driving intelligent, efficient transport network operations.

URN: C25.5.859

Project details

PRISM-AI

Modern telecom networks face persistent challenges in fault detection and resolution due to fragmented operational data and loosely coupled system dependencies across heterogeneous domains. Traditional monitoring systems, reliant on inventory data traversing multiple intermediaries, suffer from latency, inconsistency, and contextual loss—hindering effective impact analysis. Challenges with heterogenous domain: * Fragmented Operational Data: Data related to devices, services, and customers is scattered across multiple systems, making it hard to maintain consistency and context. * Limited Cross-Domain Visibility: Faults that span across network domains are difficult to analyze due to loosely coupled telemetry and topology awareness. * Ineffective Impact Analysis: Without unified and real-time context, assessing the impact of faults becomes unreliable and slow. * Manual Resolution Bottlenecks: Lack of automation and intelligent correlation leads to longer mean time to repair (MTTR) and reduced service reliability. This Catalyst focuses on a transformative Agentic AI framework for intelligent fault correlation and autonomous resolution. Central to the solution are the A2A & Model Context Protocol, which enable dynamic synchronization of network inventory and topology across agents. This ensures real-time, context-rich fault and impact analysis and significantly enhances precision and responsiveness. The architecture adheres to the TM Forum Open Digital Architecture (ODA) and integrates standardized TMF Open APIs along withTMF921, TMF931 for seamless orchestration, telemetry ingestion, and incident lifecycle management. By leveraging AI to correlate cross-domain events and automate remediation, the solution aims to reduce Mean Time to Repair (MTTR) by ~ 25%-30% and elevates service reliability. A key innovation lies in consumer-facing capability wherein through Camara APIs, end-users can access real-time network insights, opening new avenues for transparency, trust, and monetization. "Our network spans multiple domains - Optical, IP, Power - each with its own tools and data silos. When issues arise, faults often cross these boundaries, making root cause isolation inefficient. By investing in cross-domain, AI-driven service assurance, we can cut false incidents and reduce mean time to repair by up to 50%, directly improving customer experience, and helping to improve Autonomous Network rating" – Utsav Jain, Senior Manager – Network Monitoring at BT The heterogenous nature of modern Fixed Network architectures has the consequence of making Service Assurance reactive, with lots of false positives and reduced Quality of Experience (QoE). Further complications result from siloed and static rule-based fault detections that lack service context. Finally, the fault resolution journey is based on decisions taken manually by network operators following sometimes outdated runbooks. The solution to the above problems lies in a holistic approach that can understand and leverage User Intent and provides AI-driven Unified Assurance with Multi-Domain Fault Correlation, real-time Network Insights, and Autonomous Resolution.

URN: C25.5.875

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Intelligent cross-domain network assurance

Intelligent Multi-Domain Cross-Disciplinary Network O&M Capability solves critical network operation failures caused by human configuration errors and cross-domain silos. Current fragmented systems result in >70% service outages from manual mistakes in multi-vendor environments, delaying fault resolution for hours. Our solution integrates four patented modules: Wing Script: Pre-change script audit via conflict detection prevents erroneous configurations. Large AI configuration models combine with small models applied in IP resource adjustment system for automated IP network vulnerability identification. Wing Simulation: Protocol behavior simulation using routing/flow inputs predicts routing/forwarding tables. Cross-vendor (Huawei) heterogeneous simulation enables full-network coverage. Wing Topology: Automatically builds real-time updated network physical topology / dynamic network service routing flow topology, enables inspection and maintenance capabilities based on service flows, predictive maintenance, and circumvents large-scale failures.Integrating end-to-end ping/trace, log analysis, and alarm correlation. Wing AI-Config:Pulls approved plans & scripts, auto-executes deployments, alerts on errors. Validates scripts against plans, restricts high-risk commands, audits execution for compliance & smarter change control. Business Impact: • Zero mass service disruptions • 80% faster MTTR • 40% OPEX reduction Innovation: First integrated AI agent merging pre-audit, multi-vendor simulation, real-time digital twin (99% accuracy), and self-healing automation – transforming siloed operations into error-proof networks.

URN: C25.5.890

Project details

Project Aura (AI + RAN)

This Catalyst project brings together Red Hat, StarHub, SynaXG and other ecosystem partners to build an AI-powered blueprint for next-generation AI-RAN and edge services. By combining OSS/BSS capabilities with edge AI applications — such as video analytics, drone orchestration, and location-based services — the project aims to demonstrate a paradigm shift on how telcos can monetize network intelligence, offer new use cases and deliver differentiated customer experiences using CAMARA API’s. Unlike traditional RAN initiatives, the focus is on real-time insights and service innovation at the network edge, bridging the gap between infrastructure and application layers. With StarHub as the regional lead, this initiative addresses the unique demands of Asia-Pacific service providers while aligning with TM Forum’s vision of open, intelligent networks. The proposed architecture integrates AI workloads, data pipelines, and orchestration on a unified platform, enabling flexibility, scalability, and ecosystem collaboration. By harnessing hybrid cloud capabilities and engaging potential partners for AI Accelerator’s, this project delivers a future-ready telco model while providing a scalable blueprint for global adoption. The expected outcome is a compelling showcase of how telcos can evolve from connectivity providers to AI-first infrastructure providers that offer innovative digital services using open platforms and edge intelligence. CSPs are driven by the need for greater efficiency, cost reduction, and new revenue streams. The current infrastructure model often involves separate, underutilized hardware for network functions and for AI applications. By running AI-RAN on a shared, accelerated infrastructure at the network edge, they can: Today, CSP networks run RAN and AI workloads on separate, often underused hardware. By consolidating onto a shared, high-performance edge platform, CSPs can: Boost network performance through AI-driven, real-time optimization. Maximize ROI by keeping expensive GPUs fully utilized for both RAN and AI tasks. Monetize the edge by offering AI-as-a-Service to enterprises. This turns the RAN from a cost center into a revenue-generating platform. From Telco to Tech Powerhouse CSPs can differentiate by offering edge-native services such as: - Generative AI-as-a-Service — low-latency assistants and chatbots hosted at the edge. - Digital twins — real-time models for predictive maintenance and optimization. - Instant analytics — actionable insights from IoT and sensor data. Instead of competing on coverage and price, CSPs become enablers of innovation for industries. Fueling Innovation Across Verticals With AI at the edge, industries can deploy capabilities previously limited by latency and bandwidth: - Manufacturing: Instant quality control with AI vision on the factory floor. - Transport: Local, secure data processing for operational safety. - Logistics: Ultra-low-latency navigation for autonomous vehicles and delivery robots. The Bottom Line This isn’t just about faster networks — it’s about redefining what networks can do. AI-RAN at the edge unlocks new efficiencies, fuels industry innovation, and opens entirely new revenue streams. The CSP of the future isn’t just a connectivity provider — it’s the backbone of the AI-powered economy.

URN: C25.5.899

Project details

TeleNavi: Voice-only navigation & ride-hailing

With internet evolving at a breakneck pace, the elderly are becoming increasingly unfamiliar with mobile phones. Many of them are unable to use E-maps, GPS navigation, and ride-hailing apps, even smartphones, which puts them at a competitive disadvantage of being difficult to hail a cab on the roadside for a long time. The “Digital Travel Dilemma” traps the lifestyle and restricts the quality of life and the consumption level of the elderly. Due to the difficulty in locating users and the high costs and low efficiency of human customer service or audio order listening by taxi drivers, the current use and promotion of ride-hailing service hot line are very challenging. TeleNavi is the world’s first "Voice-Only Location and Navigation Tech and Service ", designed for elderly users, international travelers, and those in low-network-coverage areas, delivering seamless travel assistance through voice positioning. Leveraging TMF Open API, GSMA Open Gateway API and AI LLM, TeleNavi enables voice-only positioning and ride-hailing services via phone calls, making travel more convenient and inclusive. No apps, no GPS, no 4/5G mobile data, no smart devices and no complicated steps, just a basic feature phone to make a simple phone call can solve it all.

URN: C25.5.898

Project details

Multi-agents powering 5G-A growth

Communication Service Providers (CSPs) and vertical markets are grappling with a core challenge: how to monetize the significant investments in 5G-Advanced (5G-A) networks. The true value of 5G-A lies not in basic connectivity, but in enabling a new class of high-value, immersive services like real-time AR/VR, smart manufacturing, and AI-driven applications. The business pain points are twofold: Operational Inefficiency: Traditional, manual network management cannot handle the complexity and dynamic demands of these new services. Launching a new service is a slow, costly, and resource-intensive process, leading to a high barrier to entry and slow time-to-market. Lack of Experience Assurance: CSPs currently lack the granular visibility and automation needed to guarantee a high-quality user experience (QoE) for every customer, which is critical for retaining users and securing service-level agreements (SLAs) with enterprise clients. Without this, they cannot charge a premium for their offerings. Solving this challenge is vital for CSPs to avoid becoming a "dumb pipe" and to become a strategic partner to vertical industries. It transforms their business by enabling a shift from a low-margin connectivity model to a high-value, assured-service model. They can offer dynamic, intelligent packages with performance guarantees, unlocking new revenue streams and increasing ARPU (Average Revenue Per User). As a Senior Director of Mobile Networks at a leading CSP puts it: "The true value of 5G-A isn't just speed; it's about enabling a new class of immersive and intelligent services. Our biggest challenge is managing the complexity and ensuring a flawless experience for every user, every time. Without that capability, we simply can't deliver on the promise of 5G-A and compete effectively."

URN: C25.5.903

Project details

AI marketing brain in telecoms

In an era where over 70% of CSPs struggle with fragmented data and static customer profiles, the AI Marketing Brain introduces a transformative solution. By leveraging a Large User Model (LUM) built on Graph Neural Networks (GNNs) and Transformer-based AI, this Catalyst enables real-time, hyper-personalized marketing strategies. The system integrates multi-domain data (e.g., CRM, billing, network usage) to predict user behavior, automate campaign execution, and optimize pricing dynamically. Unlike traditional marketing, which relies on manual workflows and delayed analytics, the AI Marketing Brain reduces decision latency to seconds, driving measurable outcomes like 18% ARPU growth in 5G upselling trials. This project aligns with TM Forum’s DT4DI standards, ensuring scalability across 2B/2C scenarios while addressing privacy compliance through synthetic data training. CSPs face a critical challenge: declining customer retention rates and stagnant revenue growth amid rising operational costs. For example, Telkomsel’s 5G adoption campaigns previously failed due to generic targeting and delayed feedback loops. As one executive noted, “Our marketing teams were working with last year’s data, while user behavior evolved in weeks. We needed a system that could predict churn and act before it happened.” The AI Marketing Brain directly addresses this by enabling proactive, data-driven decisions. For B2C scenarios, it reduces manual effort by 40% while increasing campaign ROI. For B2B, it streamlines FMC (Fixed-Mobile Convergence) scenarios by integrating enterprise usage patterns with consumer behavior. Solving these pain points will allow CSPs to shift from reactive cost centers to agile, revenue-generating departments. The solution seamlessly integrates operational data, business domain insights, and third-party sources to construct a comprehensive and granular customer profile. Leveraging advanced artificial intelligence models—including graph analytics, machine learning, and real-time event detection—it automates decision-making and enables large-scale personalized customer engagement. For instance, by analyzing behavioral data and usage patterns, the system can precisely identify a segment of 4G users in the courier industry and significantly enhance 5G adoption through targeted voice plan offers. Additionally, it drives higher conversion rates via automated, graph-based revenue optimization strategies.

URN: C25.5.887

Project details

Millisecond CX assurance for business growth

In the rapidly evolving telecom landscape, traditional customer satisfaction management methods struggle to keep pace with the dynamic demands of modern users. This project introduces a data-driven customer experience ecosystem that leverages AI and digital twin technologies to transform how CSPs understand, predict, and enhance user satisfaction. By integrating real-time network performance, service delivery, and behavioral analytics, the solution enables CSPs to proactively address issues, optimize resource allocation, and align customer needs with business outcomes. Unlike conventional approaches, this framework shifts from reactive feedback loops to predictive experience design, ensuring that every interaction contributes to measurable business value. CSPs face mounting pressure to deliver seamless, personalized experiences in an era where user expectations are shaped by hyper-connected digital ecosystems. Traditional methods of measuring satisfaction—such as surveys and static KPIs—are limited by: Fragmented data: Network metrics, service feedback, and user behavior remain siloed, preventing holistic root-cause analysis. Delayed responses: Reactive decision-making based on outdated feedback hinders real-time issue resolution (e.g., network latency or service gaps). Misaligned priorities: Satisfaction improvements often lack clear connections to revenue growth, making ROI justification challenging. Solving these challenges will redefine how CSPs operationalize customer experience. As Başar Günyel, Senior Manager of Network Quality at Vodafone Türkiye, states: "Our customers’ happiness and experience are our main-focus areas, and we measure this through complaints, surveys, and other feedback mechanisms. NPS surveys provide valuable insights into customer sentiment, and we leverage various network data sources to correlate this feedback with actual network performance.“ This approach to customer satisfaction management will foster a more personalized, responsive, and efficient customer experience. Ultimately, by enhancing network performance and reliability, it empowers communications service providers to proactively meet evolving customer expectations, ensuring sustained competitiveness and market leadership.

URN: C25.5.886

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AI-driven customer experience-based network investments

Mobile operators still decide network investments using sparse drive-tests, siloed OSS data, and slow manual analysis. The result is delayed fixes, overspending on CAPEX where it doesn’t lift customer experience, and OPEX tied up in fieldwork. Our Catalyst introduces a DePIN-powered, AI- driven loop that turns customer devices into a privacy-preserving sensing network and converts insights into immediate action. With explicit consent, users contribute quality-of-experience (QoE) and radio metrics via a lightweight app and receive on-chain token rewards. This creates a high-resolution, low-cost data fabric with transparent incentives and verifiable provenance. We then use the crowdsourced data with OSS/KPI, probes, and site parameters to build a network digital twin. ML models perform root-cause analysis, predict congestion weeks ahead, simulate “what-if” scenarios, and recommend zero-touch parameter changes or targeted build-outs ranked by CX gain per dollar. Operators cut drive-test costs, accelerate time-to-detect/repair, and direct CAPEX to the neighborhoods and venues that matter most—boosting NPS and revenue while reducing OPEX. End users see faster, more reliable service precisely where they live, commute, and attend events.

URN: C25.5.901

Project details

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