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November 25-27, 2025
Bangkok

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:

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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Telco AEGIS: Autonomous ecosystem for generative intelligence and security

Telco AEGIS: Autonomous ecosystem for generative intelligence and security

Telco AEGIS: Autonomous Security for a New Era of Threats Cyber threats in telecom have rapidly evolved—from simple fraud to sophisticated attacks that compromise national-level visibility and location intelligence. Traditional, static defenses can no longer keep pace. They are too slow, too reactive, and too fragmented to handle the scale and complexity of modern threats. Telco AEGIS addresses this challenge by introducing an Agentic and Autonomous Security Lifecycle, transforming security operations from manual, batch-based processes into a continuous, intelligence-driven, and governed model. Instead of relying on reactive configurations, the solution enables intent-driven decisioning, automated playbooks, and pre-deployment validation—ensuring every security action is tested, risk-assessed, and proven before reaching production. At its core, Telco AEGIS combines agentic AI with a unified intelligence layer that aggregates multi-CSP telemetry, enriched with threat intelligence and telco-specific context. Through a closed-loop lifecycle—monitoring, detecting, generating, validating, and deploying—specialized AI agents collaborate to deliver precise, context-aware security outcomes. Built on the Model Context Protocol (MCP) and aligned with TM Forum Open Digital Architecture (ODA), the solution separates decision intelligence from enforcement, enabling seamless integration across multi-vendor environments. Through automation & AI, the Catalyst enables networks to: * Reduces manual effort by over 30%. * Accelerates MTTD and MTTR. * Ensures that more than 95% of security updates are validated before deployment. It minimizes configuration errors. * Reduces false positives. * Strengthens protection against fraud and signaling abuse—while enabling faster, safer service delivery without disruption. Beyond operational efficiency, Telco AEGIS delivers broader impact by strengthening national infrastructure resilience, reducing scams, and increasing trust across interconnect and roaming ecosystems. It shifts the industry from reactive security to autonomous, evidence driven assurance where intelligence becomes the currency of trust and networks evolve into proactive, resilient digital platforms. Autonomous security. Proven outcomes. Trusted networks.

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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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ALE-X

ALE-X

The Catalyst demonstrates an Agentic AI-driven, intent-to-operate framework that unifies service activation and network change management into a single autonomous lifecycle aligned with TM Forum ODA and Autonomous Networks Level 4, with a clear evolution path to Level 5. CSPs and large enterprises manage increasingly complex hybrid networks spanning multiple domains like SD-WAN, LAN, transport etc... Service activation and network change are still treated as separate, manual, and technology-specific processes involving multiple teams, scripts, and vendor tools. This results in slow delivery, inconsistent policy enforcement, elevated operational risk, increasing cost and limited progress toward Autonomous Networks Level 4 and beyond. ""Activation is just the first change in a service lifecycle" As customers increasingly request changes directly and service volumes grow by 30–50%, CSPs require a single, trusted, policy-governed, autonomous lifecycle that can safely activate, modify, optimize, and assure services across multi-vendor environments. Enterprise customers, operations teams, or external systems submit service or change requests in natural language or via APIs. These intents are ingested through TMF921 Intent Management, where Agentic AI interprets, negotiates, and decomposes them into standardized service, resource, and policy intents. The policy-first approach for change management ensures that only compliant, low-risk configurations are approved for execution. In activation, it enables vendor agnostic activation leveraging standard network templates like OpenConfig / IETF YANG, enabling consistent, repeatable, and auditable activation across multi‑vendor, multi-domain hybrid environments Using TM Forum Open APIs, the system orchestrates zero-touch activation and change execution across multi-vendor infrastructure. TMF921 - Intent capture and normalization TMF640 – Service Activation & Configuration to execute service-level activations and modifications TMF702 / TMF664 – Resource Activation & Resource Function Activation for domain-level and network-element changes TMF655 - Change management Continuous telemetry, KPI validation, and AI-driven anomaly detection enable closed-loop assurance, with automated remediation or rollback when deviations are detected, reducing service risk, improving SLA compliance, reinforces trust in autonomous activation and change operations. By unifying intent management, policy-first activation, autonomous change execution, and closed-loop assurance, the Catalyst enables CSPs to safely scale customer-initiated changes, reduce operational effort, and deliver hybrid network services at cloud speed—providing a practical and repeatable path toward Level 4 and Level 5 autonomous operations

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URN: C26.0.929
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Driving adaptive operations in ANL4

Driving adaptive operations in ANL4

As communication service providers progress toward Autonomous Network Level 4 (AN L4), change management becomes a critical bottleneck. While AI agents are increasingly used for monitoring and optimization, network changes—such as configuration updates, capacity adjustments, and service modifications—remain largely manual, risk-averse, and slow. This limits operational efficiency and prevents CSPs from fully realizing agile, intent-driven operating models. The Managing Change in AN L4 Catalyst addresses this gap by extending the agentic AI framework to include intelligent, governed change management. The project explores how human and machine collaboration can be orchestrated to safely plan, assess, execute, and learn from network changes in an AN L4 environment, shifting change operations from static procedures to adaptive, AI-assisted workflows. The solution introduces an agent-driven change orchestration approach, leveraging chain-of-thought reasoning to evaluate change intent, assess risk and impact, recommend actions, and coordinate execution across domains. Rather than replacing human oversight, the framework enables progressive delegation—allowing AI agents to manage low-risk, repeatable changes autonomously while keeping humans in the loop for high-impact or exceptional scenarios. Aligned with TM Forum Autonomous Network principles, the Catalyst defines a structured methodology and performance metrics for AI-assisted change management. Success is measured across four dimensions: execution reliability, safety and compliance, operational efficiency and velocity, and system intelligence and learning. These metrics provide CSPs with a clear, measurable path to scaling automated change while maintaining trust and control. By transforming change management into an intelligent, collaborative process, the Catalyst enables CSPs to increase operational efficiency, reduce risk, and accelerate the transition to truly autonomous, agile network operations at AN L4.

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URN: C26.0.973
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Perception driven broadband network energy efficiency solution

Perception driven broadband network energy efficiency solution

The Perception-Driven Broadband Network Energy Efficiency Solution addresses one of the most critical challenges facing the broadband industry: how to reduce rapidly rising energy consumption and carbon emissions without compromising network performance, user experience, or computing power quality. Bringing together operators, equipment vendors, IDC service providers, and research institutions, the Catalyst delivers a coordinated, end-to-end approach to green and sustainable digital infrastructure. As 5G base station deployments scale and data centers and intelligent computing facilities become primary drivers of electricity demand, the industry faces an “energy consumption triangle”: surging energy costs, fragmented optimization across network and data center domains, and energy-saving measures that often degrade service quality. This Catalyst responds by introducing a new paradigm of experience-oriented energy efficiency, enabling energy conservation that is driven by real-time service perception and system-level optimization rather than isolated, component-level controls. The solution is built on one unified framework and three scenario-specific pillars. A network-computing-energy synergy framework establishes a global, end-to-end energy efficiency model spanning user terminals, access and transmission networks, cloud data centers, and intelligent computing centers. Energy management is deeply integrated with service and computing-power scheduling, allowing optimization decisions to be made at the system level rather than within individual silos. Three precision pillars address the industry’s highest energy-consumption scenarios. For 5G/4G base stations, AI-driven service awareness and traffic prediction dynamically adjust antenna power, carrier activation, and symbol-level shutdown strategies, achieving cell-, user-, and service-level energy savings while preserving high-value service experience. For traditional data centers, advanced cooling technologies combined with AI-based load-to-cooling coordination drive PUE toward best-in-class levels below 1.2. For intelligent computing data centers, elastic and green AIDC architectures optimize computing, cooling, and airflow, and schedule non-urgent training workloads during off-peak periods to maximize green energy usage and reduce energy consumption per computing task. Success is measured through tangible business and sustainability outcomes: 15–25% reduction in 5G base station energy consumption, data center PUE optimized to below 1.3, and 10–15% lower unit energy consumption in intelligent computing centers—all while ensuring high-value service KPIs degrade by less than 5%. At scale, the solution is expected to reduce annual carbon emissions by more than one million tons, directly supporting dual-carbon goals. By aligning energy efficiency with user experience and computing quality, this Catalyst establishes a scalable, perception-driven blueprint for the green and low-carbon transformation of broadband networks—enabling sustainable growth for the digital infrastructure of the future.

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URN: C26.0.979
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LIA FieldOps: Autonomous AI agents for field technician support

LIA FieldOps: Autonomous AI agents for field technician support

LIA FieldOps introduces a new operational paradigm for communications service providers by placing autonomous AI agents at the center of field operations. Designed to act as the first operational decision layer for field technicians, LIA FieldOps reduces dependency on centralized Operations Centers, accelerates incident resolution, and enables a scalable path toward zero-touch field operations. Field operations are among the most costly and human-dependent domains in telecom. Technicians routinely rely on NOC and CO teams for troubleshooting guidance, authorization, and procedural support—creating bottlenecks that increase Mean Time to Repair (MTTR), limit workforce productivity, and drive up operational costs. LIA FieldOps directly addresses this challenge by providing real-time, natural-language operational support that safely transfers decision-making from humans to AI. Unlike traditional chatbots or rule-based assistants, LIA FieldOps operates as a context-aware, autonomous operational agent. It combines generative AI, structured operational playbooks, historical ticket intelligence, and live conversational context to diagnose issues, guide technicians through complex procedures, and autonomously resolve incidents when confidence thresholds are met. When uncertainty is detected, LIA performs an intelligent, structured handover to human engineers, preserving full diagnostic context, actions taken, and decision rationale—eliminating rework and reducing handling time. The solution is autonomy-by-design, continuously evaluating decision confidence using contextual signals, historical outcomes, and operational rules. A built-in learning loop ensures that every interaction strengthens the operational knowledge base, increasing autonomous resolution rates over time while maintaining strict safety, governance, and auditability. Architecturally, LIA FieldOps is a composable, API-driven platform aligned with TM Forum Open Digital Architecture (ODA) and integrated through TM Forum Open APIs with OSS/BSS, ticketing systems, and network management platforms. The solution has already been validated in a live Tier-1 CSP environment, demonstrating measurable reductions in human escalations even prior to full system integration. By reducing escalations, lowering MTTR, increasing technician productivity, and cutting operational costs, LIA FieldOps enables CSPs to decouple field productivity from centralized human availability. More importantly, it provides a controlled, measurable pathway toward Autonomous Networks Level 4, redefining how operational decisions are made and positioning AI agents as trusted, governed operational entities within the telecom ecosystem. LIA FieldOps does not simply automate field tasks—it transforms field operations into an autonomous, resilient, and scalable capability for the next era of telecom operations.

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URN: C26.0.971
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The butler did it: Turning telco infrastructure into AI services

The butler did it: Turning telco infrastructure into AI services

This Catalyst demonstrates how communications service providers (CSPs) can transform their network, edge, and compute assets into AI-native, outcome-driven services through XAaS (X Agents as a Service). Instead of selling undifferentiated connectivity, CSPs expose “Butlers” — autonomous, agentic services that deliver guaranteed business outcomes by orchestrating 5G/6G networks, core functions, edge cloud, and hyperscale compute. Across verticals such as aviation, logistics, energy, public safety, retail, mining, and transport, Butlers deliver assured outcomes like real-time monitoring, passenger flow optimization, remote operations, and event-driven public safety. Each Butler dynamically combines connectivity, policy control, edge AI, and compute to meet SLA-backed performance targets, enabling enterprises to buy outcomes rather than bandwidth or static network products. The Catalyst addresses a critical industry gap: enterprises are rapidly adopting AI-native operations and demand deterministic outcomes with accountability, while CSPs remain constrained by legacy service creation, assurance, and monetization models. XAaS closes this gap through agentic intent translation, end-to-end orchestration, and outcome-based monetization aligned with TM Forum ODA. This allows CSPs to confidently design, quote, deliver, and monetize AI services using event- and outcome-driven billing. What makes the solution innovative is its shift of AI from an internal efficiency tool to a revenue-generating service layer. Customers pay only when outcomes are achieved, supported by a standardized Agentic Monetization Fabric spanning engagement, integration, commerce, and cloud runtime layers. The inclusion of a non-telco Enterprise Champion further grounds the solution in real buyer needs and validates commercial viability. Success is measured by the ability to shift CSP revenue from low-margin connectivity to high-margin AI services, accelerate time-to-market for new Butler offerings, improve enterprise intent accuracy and fulfillment speed, and increase enterprise adoption, retention, and SLA compliance. Ultimately, the Catalyst positions CSPs to capture the AI value layer and re-establish relevance as trusted providers of assured, AI-native services in the digital economy.

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URN: C26.0.966
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Value-driven agentic AI marketplace for mega events

Value-driven agentic AI marketplace for mega events

This Catalyst demonstrates how communications service providers (CSPs) can deliver seamless, high-performance connectivity for mega events through a value-driven, agentic AI Marketplace. Large-scale events span multiple venues and involve complex, multi-vendor environments across stadiums, transport corridors, broadcast hubs, and public spaces. Today, fragmented OSS/BSS processes and manual coordination make it difficult to provision and operate advanced services such as 5G network slices, private networks, DAS, Wi-Fi, and edge computing—leading to delays, SLA breaches, and lost revenue opportunities. The proposed solution introduces a multi-agent AI Marketplace where autonomous AI agents represent vendor capabilities and collaborate under defined policy guardrails. Using TM Forum Open Digital Architecture and Open APIs, agents dynamically compose, order, and operate event-specific connectivity solutions in real time. An agentic orchestrator negotiates bids from domain agents, validates compliance through policy agents, and triggers provisioning across partners, while monitoring agents continuously adapt services to changing conditions such as crowd surges or latency drift. This enables rapid, resilient, and SLA-assured delivery of mission-critical event services. Innovation lies in combining agentic orchestration with marketplace economics. The platform supports usage-based, outcome-based, and subscription monetization models, enabling CSPs to monetize premium slices, edge compute, immersive fan experiences, and data products. Governance and safety guardrails ensure controlled autonomy, with human-in-the-loop oversight for critical decisions. Beyond technology, the Catalyst drives organizational transformation by introducing AI agents as digital co-workers, shifting teams from manual coordination to AI-assisted ecosystem delivery. Success is measured by the ability to orchestrate multi-vendor agents at scale, dramatically reduce provisioning time, maintain broadcast-grade performance, and ensure compliance across dynamic event environments. Ultimately, the Catalyst provides a reusable, standards-based blueprint for CSPs to evolve from connectivity providers into ecosystem orchestrators—unlocking new revenue streams, accelerating time-to-value, and delivering exceptional experiences for event organizers, broadcasters, and fans.

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URN: C26.0.970
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Displaying 1-12 of 57 results