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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.

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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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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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Conflict management in intent-based networks - Phase II

Conflict management in intent-based networks - Phase II

As networks evolve toward autonomous, intent-driven operation, Communications Service Providers face a critical challenge: how to detect, analyse, and resolve conflicts between multiple autonomous entities acting simultaneously. These conflicts—arising from competing intents, overlapping policies, or resource contention—can lead to service degradation, instability, or unintended behaviour if not managed proactively. The Conflict Management in Intent-Based Networks Catalyst project demonstrates a framework for ensuring safe, predictable, and coordinated operation across autonomous network functions. Building on previous Catalyst work in end-to-end intent-based service realisation, this project shows how CSPs can introduce automated conflict detection, classification, and resolution mechanisms into their intent-driven architectures. The solution uses autonomous engines to evaluate intents, analyse the impact of policy changes, and identify conflicting actions across layers and domains. It then applies rule-based and AI-driven strategies to propose or execute optimal resolutions, maintaining service quality and intent compliance even in complex multi-agent environments. By addressing one of the biggest operational risks in autonomous networks, this Catalyst equips CSPs with the tools needed to adopt intent-based operations confidently and safely, accelerating the journey toward fully autonomous networks while protecting customer experience and network integrity.

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URN: C26.0.930
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Agentic network resilience and lead to quote using AI-driven digital twin

Agentic network resilience and lead to quote using AI-driven digital twin

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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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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AI-native at scale: Elevating network optimization to CX

AI-native at scale: Elevating network optimization to CX

BACKGROUND In the fiercely competitive telecommunications industry, customer experience has become the core metric for Communications Service Providers (CSPs) to consolidate market share and achieve sustainable development. According to the GSMA 2025 Mobile Economy Report, global individual mobile user penetration will only register marginal growth over the next five years. This compels operators to shift their strategy from scale expansion to experience refinement, retaining users and driving growth by delivering superior service experience. CHALLENGE However, with the rapid rise of AI applications, ultra-high-definition video, live streaming, cloud gaming and other services, user expectations for network experience continue to escalate. Traditional network optimization only focuses on conventional network KPIs, and suffers from obvious limitations in user experience optimization — including difficult analysis workflows, long turnaround time and unsatisfactory improvement results. SOLUTION To address the core demands of telecom operators, this project launches the industry’s first vertical large model solution for network optimization built on the AI-Native Framework. Oriented toward tangible business outcomes and driven by digital twins together with domain-specific professional models, it enables a paradigm shift in operations and maintenance: transforming from humans executing and closing tasks with tools to humans supervising and augmenting AI Agent-driven task execution and closed-loop management, ultimately evolving toward the advanced stage of Agentic Operations. The solution improves key performance indicators including Net Promoter Score (NPS), user churn rate, top-tier OTT experience and complaint handling duration. It also deeply integrates into operators’ daily operational scenarios, builds a digital employee AI assistant matrix empowered by domain-specific large models, and delivers end-to-end intelligent upgrading of O&M operations. Built on China Telecom Qiming Large Model foundation, the solution leverages full-scale experience data collected by intelligent radio network elements, and incorporates a newly upgraded radio network optimization domain-specific large model. Combined with scenario-based capabilities of digital employees, it drives the transformation of network optimization logic from expertise-driven to data-and-AI-driven, shifting optimization priorities from pure network indicators to end-user experience. Timely optimization of dynamically changing wireless networks has long been a persistent industry challenge. As the core engine of the solution, the radio network optimization dedicated large model relies on full-scale data collection and automatic document aggregation capabilities of intelligent radio network elements. It adopts two Transformer-based domain professional sub-models to form a closed-loop service experience optimization system:The User Experience Diagnosis Large Model (UELM) accurately identifies user experience anomalies through intelligent analysis of full-dimensional data from intelligent wireless networks.The Beam Space Large Model (BSLM) automatically completes problem diagnosis, simulation deduction and global optimization scheme generation. Optimized policies are directly delivered and enforced on live networks via digital employee assistants, achieving immediate network performance improvement and effective mitigation of potential complaint risks. This fully materializes the vision of shifting from users adapting to networks to networks proactively adapting to users. IMPACT Empowered by the disruptive design of the AI-Native Framework, the project delivers remarkable results across three dimensions to form a closed-loop value system: Outcome Delivery: Centering on core user demands, it achieves breakthrough improvement in key experience indicators. The average processing time of user complaint tickets is reduced by 37.6%, quality optimization indicators rise by 25%, and overall customer satisfaction is greatly enhanced. Domain-specific Digital Twin & Large Model Empowerment: Endowed with in-depth understanding of network mechanisms via the radio optimization vertical large model, the solution derives globally optimal overall schemes through simulation. It significantly reduces repetitive manual analysis and on-site testing, cutting on-site verification workload by over 50% in pilot areas, boosting radio optimization efficiency by more than 10 times, and substantially lowering operational costs. Operational Paradigm Upgrade: The entire user complaint handling process is greatly streamlined, enabling VIP complaint resolution within one hour. The automatic processing rate of poor-quality network optimization tickets increases by 11.2%, realizing the upgrade from passive problem response to proactive prediction and autonomous remediation. TM Forum Assets Used & Contributed Aligned with the TM Forum Open Digital Architecture (ODA), this project has deeply contributed to multiple TM Forum AIOps and DT4DI standards through practical implementation. It clarifies the core value and key application path of Domain Digital Twin (DTN) and domain large models within the AI-Native Framework, providing a replicable and scalable practical model for the AI-Native transformation of the global telecommunications industry。

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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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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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AI-driven network monetization

AI-driven network monetization

As mobile markets reach saturation and ARPU growth stalls, communications service providers must evolve from selling connectivity to monetizing differentiated, user-perceivable experiences. Despite unprecedented network capabilities, investments in 5G-Advanced and edge infrastructure often fail to translate into revenue because performance improvements are invisible to customers and disconnected from commercial activation. The AI-Driven Network Monetization Catalyst introduces an AI-enabled framework that productizes atomic network capabilities—such as guaranteed throughput, ultra-low latency, reliability, and edge compute—into tiered, SLA-backed experience offers (e.g., Gaming Ultra Mode, Live Streaming Pro, Business Travel Roaming+). By embedding business intent directly into network operations, the Catalyst enables CSPs to engineer, predict, and monetize customer experience in real time. At the core of the solution is an AI-enhanced digital twin that fuses real-time network KQIs with service telemetry, behavioral analytics, and lightweight experience feedback to model user-level experience continuously. Unlike traditional NPS or CEI approaches that react after service degradation, the system anticipates experience risks before they impact perception and proactively orchestrates network resources. These predictive actions are tightly coupled with closed-loop monetization workflows, triggering contextual upsell or experience protection for high-value moments. Aligned with TM Forum’s Open Digital Architecture and Open APIs, the Catalyst demonstrates how predictive experience management and network capability exposure can be operationalized at scale across OSS, BSS, and policy control domains. Success is measured through tangible business outcomes, including ARPU uplift, NPS improvement driven by proactive resolution, and reduced silent churn—directly linking network performance to revenue growth. By transforming superior network infrastructure into differentiated, monetizable experiences, the AI-Driven Network Monetization Catalyst provides CSPs with a scalable blueprint to move beyond utility connectivity and unlock sustainable value in saturated markets.

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URN: C26.0.977
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