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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

An experience-centric AN L4 solution providing end-to-end user experience assurance

An experience-centric AN L4 solution providing end-to-end user experience assurance

This Catalyst delivers an experience-centric Autonomous Network (AN) Level 4 solution that transforms how Communications Service Providers (CSPs) assure end-to-end user experiences across complex 5G environments. As networks evolve to support increasingly demanding digital services, traditional operations approaches based on network KPIs alone are no longer sufficient to guarantee customer outcomes. The project introduces an intelligent, AI-driven assurance framework that focuses on the quality of experience (QoE) delivered to end users, enabling CSPs to provide differentiated, predictable, and business-critical service experiences at scale. At the heart of the solution is an innovative RAN intelligent agent platform powered by advanced wireless knowledge models, simulation capabilities, and large language model technologies. The platform delivers proactive assurance across the entire service lifecycle, from pre-event planning and prediction through live operational management to post-event evaluation. By leveraging AI-driven resource allocation, predictive analytics, and automated optimisation, the solution enables CSPs to anticipate potential issues before they impact customers, rapidly identify and resolve emerging service degradations, and continuously optimise network performance based on real-time experience insights. The business value of this approach is significant. CSPs can move beyond reactive network management and towards proactive, experience-led operations that improve customer satisfaction, reduce operational costs, and strengthen service differentiation. For enterprise and industry customers, the solution provides more reliable and predictable network performance, supporting critical digital applications and accelerating adoption of advanced 5G-enabled services. The ability to prioritise users and services dynamically also creates opportunities for new premium offerings built around guaranteed experience levels rather than traditional connectivity metrics. Success is measured through tangible operational and business outcomes. The solution delivers predictive fault detection with high accuracy, enabling issues to be addressed before users are impacted. Intelligent root-cause analysis and automated network optimisation reduce service restoration times while maintaining user experience during disruptions. Real-time experience monitoring combined with digital twin simulation provides continuous visibility into network and service performance, helping operators identify high-value investment opportunities, improve return on investment, and build a foundation for autonomous, experience-driven network operations.

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URN: C26.5.1022
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Agent-to-agent protocol for telecoms – Phase II: Reliable multi-agent collaboration in the AN-L4 era - Phase II

Agent-to-agent protocol for telecoms – Phase II: Reliable multi-agent collaboration in the AN-L4 era - Phase II

As communications service providers advance towards AI-driven autonomous networks, trusted collaboration between intelligent agents has become a critical requirement for achieving higher levels of network autonomy. Agent-to-Agent Protocol for Telecoms – Phase II: Reliable Multi-Agent Collaboration in the AN-L4 Era addresses one of the industry's key challenges: enabling AI agents from different vendors and domains to collaborate securely, transparently and reliably within production environments. Building on the foundations established in Phase I, the project enhances telecom-specific Agent-to-Agent (A2A) collaboration by introducing advanced authorisation and observability capabilities that strengthen trust, coordination and governance across complex multi-agent ecosystems. The innovation lies in extending generic A2A protocols with telecom-grade reliability features specifically designed for autonomous network operations. Through the introduction of Authorization-T and Observability-T, the solution delivers fine-grained access control, cross-vendor trust management, comprehensive auditability and end-to-end traceability of agent interactions. Unlike traditional application-layer approaches, these protocol-native enhancements embed security, governance and operational visibility directly into the collaboration framework, aligning with TM Forum Autonomous Network standards and providing a scalable foundation for AN Level 4 multi-agent operations. From a business perspective, the project enables communications service providers to overcome key challenges currently limiting the adoption of AI-powered automation. By providing full audit trails, rapid fault localisation and comprehensive visibility into multi-agent decision-making processes, operators can reduce operational risk, improve compliance and strengthen confidence in autonomous actions. The ability to monitor latency, token consumption and collaboration effectiveness also helps optimise AI operating costs while ensuring predictable performance as agent-based automation scales across increasingly complex network environments. Ultimately, this Catalyst unlocks the commercial potential of agent autonomy by making multi-vendor AI ecosystems secure, trustworthy and operationally manageable. The solution supports faster adoption of autonomous operations, reduces integration complexity and establishes the governance framework required for large-scale multi-agent collaboration. By enabling reliable, standards-based communication and coordination between intelligent agents, the project accelerates the industry's journey towards AN Level 4 autonomous networks while delivering measurable improvements in operational efficiency, resilience and business agility.

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URN: C26.5.1023
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Vision 2030: Smart campus network autopilot

Vision 2030: Smart campus network autopilot

As universities accelerate digital transformation, campus networks face growing pressure to support bandwidth-intensive applications, deliver seamless user experiences, and reduce operational complexity. Vision 2030: Smart Campus Network Autopilot addresses these challenges by creating an autonomous smart campus network that combines ultra-broadband connectivity, real-time network visualization, and AI-driven decision-making in a unified platform. The project brings together Wi-Fi 7, digital twin technology, and intelligent network automation to transform how campus networks are managed. By providing up to four times greater bandwidth, immersive visibility into network performance, and AI-powered fault detection and resolution, the solution enables educational institutions to support advanced learning environments, including 4K and VR-based teaching, large-scale research collaboration, and data-intensive academic services. At the heart of the solution is an intelligent network agent that continuously monitors network conditions, identifies issues, recommends actions, and supports autonomous operations. This shifts network management from reactive troubleshooting to proactive optimization, reducing fault identification and recovery times while improving service reliability and operational efficiency. Beyond enhancing connectivity, the project demonstrates how autonomous networks can become strategic enablers of innovation. Intelligent network insights can support sustainability initiatives, optimize energy consumption, and create new opportunities for digital campus services. By aligning with the TM Forum Autonomous Networks Mission and supporting the goals of Saudi Arabia's Vision 2030, the Catalyst showcases how AI-powered networking can help educational institutions build smarter, more resilient, and future-ready campuses.

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URN: C26.5.1010
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PRISM-AI Phase III

PRISM-AI Phase III

PRISM-AI Phase III accelerates the telecom industry's journey towards Autonomous Networks by unifying operational assurance, sustainability, and Agentic AI into a single intelligent closed-loop solution. Built on the proven foundation of previous PRISM-AI phases, the project extends beyond fault resolution and service experience management to address one of the industry's most pressing challenges: achieving net-zero objectives while maintaining network reliability and operational efficiency. By transforming sustainability from a reporting activity into a real-time operational capability, PRISM-AI enables communications service providers (CSPs) to improve network performance, reduce costs, and lower carbon emissions simultaneously. At the heart of the innovation is a powerful new approach that uses a single power-domain IoT signal to deliver multiple business outcomes. Telemetry from batteries, rectifiers, cooling systems, and energy consumption not only predicts degradation-based faults before they impact services, but also identifies opportunities for energy optimisation. This eliminates the traditional separation between network operations and ESG initiatives, allowing operators to use the same data source to improve reliability, reduce waste, and achieve measurable sustainability gains. PRISM-AI Phase III also introduces end-to-end multi-domain correlation across Power, Transmission, Edge Cloud and IP networks, addressing one of the biggest operational challenges facing modern NOCs. Instead of generating dozens of disconnected alarms for a single underlying issue, the solution correlates events across domains to identify a single root cause and accurately determine service impact. This significantly reduces alarm noise, accelerates root-cause identification, shortens repair times, and enables operators to move from reactive firefighting towards proactive, autonomous operations with greater confidence and control. The solution is completed by policy-governed Agentic AI, delivering trusted automation with full auditability and regulatory readiness. Autonomous actions are executed through controlled, least-privilege AI agents operating within defined policies and supported by immutable traceability. The result is a practical and trustworthy pathway towards higher Autonomous Networks maturity, where CSPs can reduce operational costs, achieve 15-25% energy savings, lower carbon emissions, minimise SLA breaches, and strengthen customer trust through a single coordinated investment that advances reliability, sustainability, and autonomy together.

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URN: C26.5.1011
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Autonomy accelerated: Connected intelligence for reliable agentic operations - Phase IV

Autonomy accelerated: Connected intelligence for reliable agentic operations - Phase IV

Autonomy Accelerated: Connected Intelligence for Reliable Agentic Operations – Phase IV explores how communications service providers (CSPs) can deliver the next generation of AI-enabled services that demand guaranteed connectivity, real-time responsiveness and assured service quality. The Catalyst addresses a critical industry challenge: operational silos that prevent CSPs from providing reliable, end-to-end experiences for emerging use cases such as emergency services, remote healthcare, computer vision and AI-powered edge applications. By connecting business, service, network and customer experience domains, the project demonstrates a more intelligent and coordinated approach to autonomous operations. Building on previous phases, the Catalyst extends the use of agentic AI, knowledge graphs and autonomous decision-making across a broader range of operational domains, including the Radio Access Network (RAN). A key innovation is the integration of business intent with service intent, enabling CSPs to capture commercial objectives, automatically translate them into service requirements, validate feasibility and optimise delivery across multiple domains. The addition of a service design assistant further enhances automation, helping accelerate service creation while reducing complexity and manual intervention. The solution combines agentic AI, AIOps, digital twins, knowledge graphs and closed-loop automation within a common data foundation aligned to TM Forum Open Digital Architecture (ODA) and Open APIs. Rather than focusing solely on network performance, the Catalyst enables autonomous decisions driven by business outcomes, customer experience and service objectives. Its continuous learning approach allows operational insights to improve future decision-making, resulting in faster issue resolution, proactive optimisation and greater operational resilience. The business value is significant. By advancing towards Level 4 autonomous operations, CSPs can reduce operational costs, minimise manual effort, accelerate service onboarding and improve SLA compliance. The Catalyst also creates new monetisation opportunities through AI-ready connectivity services, 5G AI slices and differentiated, SLA-backed offerings for enterprise and consumer markets. Ultimately, it provides a practical pathway for CSPs to transform from reactive network operators into intelligent, outcome-driven service providers capable of delivering measurable business value, superior customer experiences and sustainable growth in the AI era.

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URN: C26.5.1013
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Agentic AI for inter-operator composability

Agentic AI for inter-operator composability

Agentic AI for Inter-Operator Composability explores how communications service providers can dynamically coordinate and share network resources, infrastructure, and operational capabilities across organisational boundaries. Building on the foundations established through the OmniBOSS Catalyst programme, the project addresses emerging industry needs for secure, standards-based collaboration between operators in scenarios such as capacity sharing, network resilience, emergency response, and security incident management. As networks become increasingly distributed and complex, traditional approaches to coordination are no longer sufficient to deliver the speed, agility, and efficiency required. The Catalyst introduces an innovative agentic AI framework designed to enable intelligent inter-operator composability. By combining AI-driven decision-making with TM Forum standards, trust frameworks, and reusable industry assets, the solution aims to automate and optimise how operators interact, exchange information, and orchestrate services across their networks. This represents a significant step forward for the industry, moving beyond manual coordination processes towards autonomous, trusted collaboration at scale. From a business perspective, the project has the potential to unlock substantial operational and commercial value. Dynamic resource sharing can improve infrastructure utilisation, reduce unnecessary network build costs, and enable faster service restoration during outages or high-demand events. By allowing operators to collaborate more effectively, the solution supports improved customer experiences, greater network resilience, and more efficient capital investment strategies as the industry prepares for next-generation network evolution, including 6G. Success will be measured by demonstrating real-world production feasibility and quantifiable operational improvements. Key indicators include reduced time to restoration, faster fault repair, and enhanced network build-out efficiency. By proving that AI-enabled inter-operator composability can be implemented in a trusted and scalable way, the Catalyst will provide a foundation for future industry adoption and help accelerate the transformation towards more intelligent, collaborative telecommunications ecosystems.

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URN: C26.5.1006
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Agentic intelligence exchange: Trusted intelligence commerce -  Phase III

Agentic intelligence exchange: Trusted intelligence commerce - Phase III

Agentic Intelligence Exchange: Trusted Intelligence Commerce - Phase III represents the next evolution of telecom intelligence, moving beyond intelligence creation and sharing to demonstrate how trusted intelligence can be commercialised as a governed digital product. Building on the foundations established in earlier phases, the project will showcase how communications service providers (CSPs) can securely package, publish, discover, and trade intelligence products through a trusted ecosystem while maintaining strict controls around consent, permitted purpose, privacy, and data sovereignty. By creating a repeatable operating model for intelligence commerce, the project aims to unlock entirely new opportunities for collaboration between CSPs and enterprise partners. At its core, the Catalyst introduces an innovative Intelligence Product Commerce Framework that treats intelligence as a marketable asset with clearly defined pricing, quality standards, usage rules, auditability, and service levels. Through an end-to-end commercial journey covering catalogue publication, quotation, ordering, consumption, metering, revenue attribution, settlement, and audit, the project will demonstrate how AI-powered intelligence can be exchanged securely and transparently across multiple organisations. Agentic AI and TM Forum Open APIs provide the foundation for automating decision-making, enforcing governance policies, and ensuring explainable outcomes throughout the process. The business value is significant for both CSPs and enterprises. CSPs can move beyond traditional connectivity services and internal marketing campaigns to become trusted intelligence providers, creating new B2B2X revenue streams without exposing customer data. Enterprise organisations gain access to high-value intelligence products that support fraud prevention, identity verification, customer engagement, and digital trust initiatives through a single, secure integration model. By enabling intelligence consumption across multiple CSPs, the solution also reduces operational complexity, accelerates onboarding, and simplifies commercial relationships across the ecosystem. The project's broader vision is to establish a new category of telecom commerce where intelligence is exchanged as securely and efficiently as network services are today. By demonstrating governance, consent management, policy enforcement, revenue sharing, and quality assurance at scale, Phase III provides a practical blueprint for the future AI economy. The result is a trusted marketplace where CSPs retain sovereignty over their data, enterprises gain actionable intelligence, and ecosystem orchestrators such as Telin can create value by connecting providers and consumers through a secure, commercially viable intelligence exchange.

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URN: C26.5.1016
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Knowledge-driven root cause analysis for faster recovery

Knowledge-driven root cause analysis for faster recovery

From Data to Resolution: Agentic AI and the Network showcases how communications service providers can move beyond traditional monitoring and manual fault investigation to a new era of intelligent, knowledge-driven operations. As networks become increasingly complex, resolving issues quickly and accurately remains heavily dependent on specialist expertise, resulting in slower response times and inconsistent outcomes. This Catalyst addresses that challenge by transforming operational data into actionable intelligence, enabling faster root cause analysis (RCA), improved service resilience, and more consistent customer experiences. At the core of the solution is an innovative knowledge plane that continuously captures alarms, topology data, service intent, incident records, and operational expertise into a semantic knowledge graph. By connecting previously fragmented data sources across network and IT domains, the platform creates a shared source of operational intelligence. Agentic AI-powered RCA assistants can then reason over this knowledge in near real time, identifying causal relationships, assessing service impact, and recommending the most effective resolution actions based on historical experience and current network conditions. What makes the Catalyst truly innovative is its combination of ontology-driven reasoning, knowledge management, and agentic AI orchestration. Instead of analysing faults in isolation, the system leverages reusable organisational knowledge, known remediation playbooks, and contextual network intelligence to accelerate diagnosis and recovery. The result is an explainable and trustworthy approach to automation, where engineers can understand the reasoning behind recommendations while progressively increasing the proportion of faults that can be resolved with minimal human intervention. The business value is substantial. By reducing Mean Time to Detect (MTTD) and Mean Time to Repair (MTTR), CSPs can minimise service disruption, protect revenue, and reduce the operational costs associated with major incidents. Improved RCA accuracy lowers the risk of repeat faults and misdiagnosis, while cross-domain visibility removes silos between RAN, core, transport, OSS/BSS, and IT environments. Aligned with TM Forum standards and designed to remain vendor-agnostic, the Catalyst provides a practical pathway from data-driven network operations to autonomous, scalable, and knowledge-powered fault resolution.

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URN: C26.5.1004
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