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November 17-19, 2026
Bangkok, Thailand

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

AI-powered end-to-end solution for customer experience – Phase II

AI-powered end-to-end solution for customer experience – Phase II

This Phase II Catalyst delivers an AI-powered, end-to-end customer experience (CX) intelligence platform that fundamentally realigns telecom network investment, operations, and customer outcomes. Today, CSPs face a persistent disconnect: strong network KPIs reported by technology teams coexist with stagnant NPS, rising churn, and inefficient allocation of over USD 200B in annual CAPEX. Technical excellence alone is no longer sufficient—investment decisions must be guided by the customer’s lived experience. Building on successful Phase I pilots, this project advances to full-scale commercial deployment by making CX the unifying metric across CTO, CMO, operations, and finance functions. The solution introduces the industry’s first fully integrated CX-to-CAPEX intelligence platform, powered by a coordinated multi-agent AI architecture and LLM-based interfaces that democratize complex network and investment data across the organization. The platform fuses real-time OSS network performance, crowdsourced customer experience signals, and predictive traffic forecasts to eliminate siloed decision-making. Agentic AI enables Level 4 autonomous operations—automating detection, root-cause analysis, self-healing, and ROI-ranked investment recommendations—while closed-loop feedback continuously validates post-investment CX improvements. LLM interfaces allow all stakeholders, from customer care to CFOs, to query the system in natural language and receive contextual, business-relevant insights. By shifting from reactive monitoring to proactive value creation, the solution targets 10–15% CAPEX optimization through smarter investment allocation, 30–50% OPEX reduction via AI-driven virtual diagnostics, 30–40% faster mean time to resolution, a 15–20% reduction in network-related churn, and a 5–10 point uplift in NPS. Collectively, these outcomes realign the CSP business engine to drive sustainable growth through superior customer loyalty and operational efficiency. The project is fully aligned with TM Forum’s ODA and Autonomous Networks missions, leveraging TM Forum Open APIs (TMF628, TMF629, TMF638) and contributing learnings to IG1444 on Agentic AI. It demonstrates how AI agents can autonomously optimize not only network performance, but also investment accountability and customer-centric business outcomes at commercial scale.

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URN: C26.0.964
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The big deal - Phase II

The big deal - Phase II

The Big Deal – Phase II builds on the success of the previous Catalyst to tackle one of the most persistent challenges in B2B telecom: the complexity of quoting, configuring, and ordering enterprise services at scale. Despite ongoing digital transformation efforts, many Communication Service Providers (CSPs) still rely on manual quoting processes for complex enterprise deals. This results in slow response times, lost opportunities, unvalidated configurations, costly manual rework, and revenue leakage when orders must be adjusted post‑sale. At the same time, rigid product definitions and inflexible catalogs make automation difficult, turning transformation initiatives into long, expensive programs. What This Catalyst Delivers This Catalyst demonstrates a new, end‑to‑end approach to enterprise product commercialization—moving from manual, error‑prone processes to fully automated, intent‑driven quoting and ordering. At the heart of the solution is a runtime, TM Forum–compliant catalog capable of modeling even the most complex enterprise products and their relationships. By introducing new catalog modeling patterns and AI‑assisted product ingestion, CSPs can rapidly productize offers, automate quoting and fulfillment, and dramatically reduce time‑to‑market and time‑to‑transform. Key Innovations Intent‑driven digital and assisted channels Customers interact through intuitive, intent‑based self‑service channels, while sales teams use advanced solutioning tools for assisted selling—removing complexity from the customer experience. AI‑accelerated product modeling AI ingests existing product specifications and documentation to automatically generate catalog models, enabling rapid onboarding of products and faster transformation of legacy portfolios. Advanced catalog composability and relationships New modeling patterns manage complex dependencies across products and services, providing guardrails for fulfillment and enabling goal‑seeking automation and AI‑driven orchestration. Supplier and access option intelligence A supplier scanner matches customer intent to the best third‑party access options by geography, enabling optimal commercial and technical decisions. One product, many markets A single catalog model supports multiple markets with different currencies, pricing, regulations, languages, and feature availability—dramatically improving global scalability.

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URN: C26.0.967
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ODA prism: Recommending the ultimate telecom plan - Phase II

ODA prism: Recommending the ultimate telecom plan - Phase II

Phase II of this Catalyst advances our mission to help telecom providers thrive in an increasingly competitive and fast-moving wireless market. As customer expectations rise and competitive offerings shift rapidly, operators struggle with limited insight, siloed processes, high churn, and slow time-to-market for new plans. It tackles those challenges head-on by delivering a real-time, intelligence-driven solution that personalizes the customer journey and enables operators to recommend the “ultimate plan” for each customer—every time. This phase extends the solution with a more scalable AI-driven architecture aligned to TM Forum’s ODA and Open APIs. The enhanced design supports additional business use cases, strengthens interoperability, and introduces next-best-action capabilities that benefit both telecom providers and their customers. At its core, ODA prism unifies disconnected value streams through a catalog-driven, P-S-R-aligned architecture and advanced customer intelligence. By combining real-time decisioning, journey orchestration, and Product-Based modeling, the solution predicts churn, identifies key moments for upsell and cross-sell, accelerates offer launch, and ensures internal and external compliance for rapid go-to-market execution. Gen-AI and Agentic AI further enhance decision accuracy with domain-specific reasoning and generative insights. Proven use cases—including personalized acquisition, price and plan optimization, and proactive churn management—demonstrate how the solution boosts customer satisfaction, increases ARPU, and strengthens lifetime value. Success will be measured by reductions in churn, increased revenue per customer, improved personalization across value chains, operational efficiencies, and dramatically faster speed to market. Ultimately, ODA prism equips operators with the intelligence and agility required to meet evolving customer needs, outperform competitors, and drive sustained business growth in the next era of wireless communications.

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URN: C26.0.917
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CX optimization via AI-driven SOC over autonomous networks - Phase II

CX optimization via AI-driven SOC over autonomous networks - Phase II

CX Optimization via AI-Driven SOC over Autonomous Networks – Phase II advances the industry’s ability to deliver consistently superior customer experience by transforming network operations from reactive support into a proactive, autonomous, and continuously optimized capability. Building on the outcomes of Phase I, this Catalyst enhances OODA-based operational architectures by introducing Digital Twins and intent-led AI agents into both the execution and analysis of Closed-Loop Automations (CLAs). In highly competitive markets, CSP differentiation increasingly depends on service quality, reliability, and the ability to anticipate and prevent customer-impacting issues. Traditional operational models struggle to manage the growing complexity of autonomous networks, often reacting to problems only after customer experience has degraded. This Catalyst directly addresses that gap by enabling predictive, intent-driven CX optimization that improves Net Promoter Score (NPS), service consistency, and operational efficiency. Phase II extends the previous solution by embedding AI agents across the full CLA lifecycle. In the first innovation layer, CLAs defined by agents, intent-based AI continuously evaluates and evolves automation logic using insights from a Knowledge Engine and simulations in Digital Twins. This ensures that automation strategies remain effective as network conditions, services, and customer expectations change. In the second layer, agents as part of CLAs, AI agents actively participate in decision-making and execution, formulating remediation plans in response to live network events, validating them through Digital Twin simulations, and iteratively refining actions before safe deployment. Successful strategies are fed back into the Knowledge Engine, enabling continuous learning and optimization. Aligned with TM Forum Open Digital Architecture (ODA), the VOF framework, and Autonomous Networks principles, the solution ensures scalability, interoperability, and measurable business value. Success is assessed through CX-centric and autonomy-driven KPIs, including improvements in NPS, perceived service quality, service stability, and customer-centric resolution times, alongside increased levels of network autonomy and reduced operational effort. By combining Digital Twins, intent-led AI agents, and closed-loop learning, this Catalyst establishes a robust blueprint for AI-driven Service Operations Centers (SOCs). It enables CSPs to systematically predict, prevent, and resolve CX issues before customers are impacted—delivering seamless, reliable, and high-quality connectivity experiences while accelerating the journey toward truly autonomous networks

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URN: C26.0.937
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Telco AEGIS: Autonomous ecosystem for generative intelligence and security

Telco AEGIS: Autonomous ecosystem for generative intelligence and security

Telco AEGIS addresses a new era of telecom threats—where attacks have evolved from fraud to compromising national‑level visibility and location intelligence. Traditional, static defences can’t keep pace. This Catalyst introduces an Agentic and Autonomous Telco Security Lifecycle, replacing manual, batch‑based operations with a continuous, intelligence‑driven, and governed security model. Built on the Model Context Protocol (MCP) and aligned with TM Forum ODA, the solution operationalizes telco security across protocols through autonomous decisioning, automated playbooks, and measurable validation before deployment. The Catalyst establishes a governed Autonomous Networks blueprint for security, separating decision intelligence from enforcement so multi‑vendor tools can plug in seamlessly. Security telemetry from multiple CSPs is ingested into a unified knowledge base, enriched with CTI, signatures, and telco‑specific data. Specialized agentic AI collaborate to monitor, detect, generate, validate, and deploy security policies through a lifecycle governed by TMF630, TMF724A, TMF688, and TMFC060. Every change is backed by objective evidence—test coverage, attack‑scenario validation, and quantified risk reduction—making “intelligence the currency of trust.” This matters because telco security remains one of the highest‑risk operational domains for CSPs. Without a lifecycle‑grade operating model, CSPs face alert fatigue, inconsistent prioritization, slow mitigation cycles, and limited post‑deployment assurance. Telco AEGIS transforms this reality by accelerating MTTD and MTTR, reducing fraud and signalling abuse losses, improving detection accuracy, and enabling safer, faster production changes. It embeds expert knowledge into reusable automated playbooks, reducing dependence on scarce specialists while improving consistency across teams, regions, and partners. The broader societal impact is equally significant: fewer scams, stronger national infrastructure resilience, and higher trust across interconnect and roaming ecosystems. Success is measured by the shift from reactive, manual operations to a continuous, autonomous, evidence‑driven lifecycle. Key outcomes include >95% of security updates deployed with pre‑deployment validation, >30% reduction in manual change effort, fewer configuration errors, reduced false positives, broader telemetry coverage, and faster zero‑day prevention. Platform success is demonstrated through portability—onboarding new CSPs without redesign—and business KPIs such as lower operational spend, improved service availability without maintenance windows, and higher confidence in security decisions. Telco AEGIS ultimately enables CSPs to evolve into proactive, resilient digital service providers equipped for the security demands of the modern telecom ecosystem.

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URN: C26.0.980
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AI+ based intelligent FBB operation enables business success - Phase II

AI+ based intelligent FBB operation enables business success - Phase II

AI+ Intelligent Fixed Broadband (FBB) Operations addresses a growing challenge faced by communications service providers: delivering consistent, high-quality home broadband experiences while reducing operational complexity and cost. Today’s FBB operations rely heavily on fragmented tools and reactive processes, making it difficult to proactively identify issues, optimise performance, and ensure customer satisfaction at scale. As broadband services become more critical to both consumer and enterprise users, these limitations directly impact business success. This Catalyst proposes an AI-driven, end-to-end intelligent FBB operations framework that leverages advanced analytics and automation to transform how broadband networks are monitored, managed, and optimised. By combining AI-based insights across network, service, and customer domains, the solution enables proactive fault detection, intelligent root-cause analysis, and predictive optimisation of broadband performance. Building on learnings from previous Catalyst phases, this project advances the solution toward greater operational maturity, focusing on real-world deployment scenarios and measurable business outcomes. Success will be evaluated through improvements in service quality, reduction in operational effort, faster issue resolution, and enhanced customer experience. The project brings together leading CSPs and technology partners to demonstrate how AI-powered FBB operations can deliver tangible value, align with TM Forum’s Open Digital Architecture principles, and provide a scalable blueprint for the wider industry.

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URN: C26.0.989
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AI decision accelerator

AI decision accelerator

Many telecom operators have invested heavily in AI, yet most deployments stop at insight and dashboards, requiring human approval before action. This limits speed, scalability, and return on investment. As industry research highlights, the real enterprise value of AI emerges when it is trusted to make and execute operational decisions—where a single, timely action can have material business impact. The AI Decision Accelerator Catalyst focuses on closing this gap by advancing AI from insight generation to authorized, production-grade decision execution. The initiative brings CSPs and technology partners together to identify, validate, and integrate high-value decision workflows where AI can safely operate within live OSS/BSS environments. Target use cases include automated customer retention and upsell actions, real-time service offer optimization based on network and behavioral context, and closed-loop network optimization in degraded areas. Rather than positioning AI as a replacement for human expertise, the Catalyst establishes a practical framework for delegating repeatable, high-frequency, rules-based decisions to AI—freeing experts to focus on strategic and complex tasks. The work centers on mapping decision scenarios with strong business impact, assessing feasibility and governance requirements, and prototyping end-to-end decision-to-action flows aligned with TM Forum Open Digital Architecture and Open APIs. Success will be measured by tangible business outcomes, including revenue uplift, churn reduction, and operational cost savings, as well as by the number and diversity of AI decision workflows that are validated for production use. Decision-to-action latency will be tracked to ensure AI acts fast enough to matter. By turning decision logic into a reusable, scalable asset, the AI Decision Accelerator helps operators move beyond isolated pilots toward an industry-wide approach for unlocking sustainable ROI from AI and embedding intelligence directly into operational execution

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URN: C26.0.978
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AI-Powered cognitive inventory and digital twin assurance

AI-Powered cognitive inventory and digital twin assurance

This Catalyst addresses one of the most persistent barriers to autonomous network operations: fragmented, inaccurate, and siloed inventory systems. CSPs today struggle with manual reconciliation, poor data quality, and limited real-time visibility across hybrid networks—issues that delay fault resolution, increase OpEx, and undermine customer trust. This Catalyst introduces an AI-driven, end-to-end inventory management foundation that unifies autonomous reconciliation, cognitive inventory assurance, an AI inventory assistant, and digital twin–based “What-If” simulation into a single, operator-ready framework. leveraging TM Forum open APIs, ODA components, and advanced AI agents, the solution automatically reconciles inventory data, predicts failures before they occur, and provides real-time operational insights with trusted accuracy. By enabling reliable, real-time, and autonomous inventory management, the Catalyst empowers operators to improve SLA compliance, reduce operational costs, strengthen business resilience, and unlock new revenue opportunities such as Network-as-a-Service (NaaS). Digital twin simulations further allow CSPs to anticipate network behavior during major incidents or natural disasters, supporting proactive decision-making and continuous service assurance. Innovative in its integration of predictive AI models, cognitive automation, and simulation capabilities, the solution delivers a unified, standards-based foundation that accelerates a CSP’s journey toward autonomous networks. With measurable improvements in reconciliation speed, predictive accuracy, SLA performance, and customer experience, this Catalyst provides the trusted inventory intelligence needed for resilient, optimized, and future-ready telecom operations.

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URN: C26.0.916
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Business-aware GNN-healing networks

Business-aware GNN-healing networks

Introduction Same fault. Different response. Not all network failures carry the same business risk. A performance degradation in a revenue-dense cell serving a financial district represents a materially different operational priority than one in a low-traffic residential zone. Yet today's autonomous networks have no mechanism to express or act on that difference. Isolating contributing factors across RAN, Core, and Cloud remains a manual and siloed process. Every fault enters the same resolution queue regardless of business impact. Business-Aware GNN-Healing Networks changes this. The catalyst introduces a three-layer closed-loop architecture: Business Intent Layer Sequences remediation based on infrastructure business criticality and revenue exposure. Graph Intelligence Layer A Graph Neural Network powered by a Google Cloud Spanner digital twin traverses cross-domain topology to identify remediation branches from a single service-layer trigger. No alarm is required. Execution Layer Vendor-agnostic remediation across any network vendor using WNR-wrapped TM Forum Open APIs. The key innovation is the first Business Intent Extension Model contributed to the TM Forum Intent Ontology (TIO). This provides operators with a standards-based vocabulary to declare which remediation branch executes first when recovery resources are constrained, decoupling business priority from network implementation. The result: same fault, different response. Level-4 autonomy across RAN, Core, and Cloud, with the business layer exploring the boundary of Level-5 through declarative, intent-driven prioritization. Validated with CSP champion data, the catalyst targets: 55% reduction in operational costs MTTR reduced from hours to minutes Protection of revenue at risk in critical coverage zones

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URN: C26.0.965
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Cyber twin: Cyber-aware ontology for AIOps

Cyber twin: Cyber-aware ontology for AIOps

Telecom operators face rapidly escalating cyber risks driven by 5G expansion, cloud-native networks, and massive device connectivity. While Security Operations Centers (SOCs) can detect threats, they lack contextual awareness of network topology, service chains, resource dependencies, and real customer impact. At the same time, Network Operations Centers (NOCs) and SOCs remain siloed, leading to slow threat triage, manual investigations, limited automation, and an inability to support autonomous operations. These challenges are further intensified by regulatory requirements such as NIS2 and DORA, which demand continuous visibility, risk analysis, and operational resilience. The Cyber Twin: Cyber-aware Ontology for AIOps Catalyst introduces a semantic, cyber-aware Digital Twin that provides contextual intelligence across network, service, and security domains. By embedding cyber knowledge into a unified ontology, the Cyber Twin autonomously discovers assets, understands service dependencies, correlates cyber events with network and customer impact, and enables AI-driven reasoning and decision-making. This cyber-aware Digital Twin transforms traditional NOC and SOC operations into a unified, autonomous model capable of closed-loop, context-aware responses. It supports AIOps-ready workflows that improve operational efficiency, enable faster and more accurate threat mitigation, and significantly reduce mean time to repair (MTTR) for network and service degradations, including those caused by security incidents. Ultimately, the Catalyst accelerates operators’ journey toward cyber-resilient autonomous networks while ensuring service continuity, customer trust, and regulatory compliance.

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URN: C26.0.963
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Spatial web: Open gateway to the immersive future - Phase II

Spatial web: Open gateway to the immersive future - Phase II

The next phase of this Catalyst advances a breakthrough industry initiative aimed at unlocking the true value of Extended Reality (XR) for Communication Service Providers (CSPs). Today, CSPs capture just 0.15% of a fast-growing $589B XR market, largely because developers lack a standardized way to access real-time network context—such as QoS, location, or identity—needed to create high-quality immersive experiences. This integration friction keeps CSP capabilities hidden and limits the growth of the Spatial Web ecosystem. Building on the foundations of Phase I and the Economy of Anchors for AR/MR, Phase II introduces the next pillar of the Spatial Web: a mixed-reality anchor economy that enables persistent, monetizable spatial experiences shared across public networks. The project combines TM Forum Open Gateway APIs, TMF Operate business logic patterns, and a proposed Decentralized Spatial Web Standard Protocol (DSSP) to transform proprietary network assets into consumable, high-value contextual services. The DSSP provides the common protocol the market lacks, standardizing how spatial nodes federate across platforms so enriched digital anchors can scale globally. This innovative framework shifts the value model from connectivity to context, enabling hyper-personalized, real-time spatial experiences and frictionless developer participation. By reducing integration costs, accelerating time to market, and establishing universal interfaces for contextual data, the project positions CSPs as central players in a Spatial Web market projected to surpass $470B by 2030. Success will be measured by increased adoption of context-aware APIs, developer uptake, API monetization velocity, and growth in high-margin, non-connectivity revenue. Phase II ultimately demonstrates how standardized network exposure and spatial protocols can unlock the immersive future—and the new value it promises for operators, developers, and users alike.

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URN: C26.0.922
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Agentic-AI powered autonomous billing dispute management

Agentic-AI powered autonomous billing dispute management

Billing disputes such as bill shock, invoice errors, and partner charge discrepancies remain one of the most manual, time-consuming, and inconsistent processes in telecom operations. Slow resolution, repetitive investigations, and human error drive customer dissatisfaction, increase churn risk, and lead to revenue leakage and high operational costs. The Agentic-AI Powered Autonomous Billing Dispute Management Catalyst introduces a lightweight, multi-agent AI solution that automates the end-to-end dispute lifecycle—from proactive detection to resolution execution. Leveraging agentic AI, the solution ensures data-backed, consistent decision-making while balancing speed, compliance, and human oversight. The platform proactively detects billing anomalies and potential disputes before customers escalate issues. It supports frictionless, omnichannel intake of complaints across chat, email, and voice, and performs autonomous root-cause analysis by correlating invoice data, billing records, mediation outputs, and partner charges. Based on this analysis, the system intelligently proposes resolutions—such as credits, adjustments, or rollbacks—and uses aggregate confidence scoring to either auto-execute actions or route them to a human-in-the-loop for approval. Built on a multi-agent architecture and integrated with BSS systems via TM Forum Open APIs, the Catalyst demonstrates how dispute management can shift from manual case handling to governed, autonomous workflows. Success is measured through improved detection and resolution accuracy, reduced handling time, higher automation and first-contact resolution rates, improved customer satisfaction, lower operational costs, and stronger revenue protection. By transforming billing dispute management into an intelligent, auditable, and autonomous capability, the Catalyst helps CSPs enh

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URN: C26.0.950
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