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GenAI Powered toolkit for network & service management

URN C24.0.648
Topics AI (Artificial Intelligence), Autonomous networks, Service orchestration
Winner

How to audit network resources in a fraction of the time with large language models

To serve customers effectively and efficiently, CSPs’ IT departments need an accurate real-time view of how their networks are performing. But the network and service resource inventory in a CSP’s operations support system (OSS) often does not reflect the current context of the network topology. This can result in costly service provisioning re-runs, impairments to the service and customer experience, and the need to reconcile data between systems and database, which takes considerable time and effort. This Catalyst is developing a generative AI-based toolkit, encompassing an adaptor agent and large language model (LLM), which will essentially mediate between the systems, processes and data in the network/service inventory database and the corresponding elements of the IP network. The solution should facilitate timely discovery of information across the network, associated network and service elements with a high degree of granularity. The overarching goal is to enhance customer experience by lowering the time needed to provision a service, and eventually enable autonomous network and service orchestration. The Catalyst plans to pilot the solution for fiber access MPLS-based IP-VPN services and 5G access services, with a view to replicating it across other services. The LLM, which will be fine-tuned across data, systems and process artifacts in relation to the network and service, will draw on the TM Forum’s business process framework and information reference model principles (such as ETOM/SID). The TM Forum assets will act as guardrails, supplemented by preventive tests for hallucination, following a significant pre-training process. The adaptive LLM will use a closed feedback loop, ingressing to the main generative AI adaptive engine, to further improve efficacy. On the operational process side, the project team will measure the service delivery time in relation to a baseline approach. Where diverse AI models are used for diverse scenarios, the team will employ A/B testing to evaluate each model’s effectiveness.

Resources

(1) TMForum Assets, theme lead review and collaboration

(1) TMForum Assets, theme lead review and collaboration

CAPABILITIES FOR REVIEW - SERVICE PROVISIONING

(2) TMF 921 to TMF 640 translation

TMF921 to TMF640 Translation

(3) FULFILLMENT Sub Project Activity Service Fulfilment

Concept Note for the Gen AI Toolkit

TM Forum Project v1

TMF-Project-Activity-(C24.0.648)

Catalyst 24-0-648 -TechM-Solution Architecture

ODA & AI integration (Paas)

Catalyst 24-0-648 - Waylay - Solution Architecture

Closed Loop AN (Autonomous Network) Architecture

(4) Scope

TMF Catalyst_PLDT Service Assurance Use Case_v1

Service Fulfillment Flow

Service Assurance

Making connectivity-as-a-service as seamless as everyday utilities

Use Cases-Decomposed

Scope of Work

(5) Final Project Submission ( Challenges, Solution , Architecture, Phases)

GenAI Powered toolkit for Network and Service Management v3

(6) TMF Catalyst 648 - Video's

GenAI Fulfilment Showcase

TechM-Intent-Provisioning-C3P

GenAI Avatar Showcase w Audio

CLA Showcase w Audio

GenAI Fulfilment Showcase w Audio

Inform feature

A new GenAI performance toolkit for cost-efficient network management

Contact team

Email the members of the Catalyst team to request more details.

Name
Email

Team members

Clarity Global Pty Ltd logo
EITC  (DU) logo
Champion
Global Wavenet Pte Ltd logo
Mobitel (Pvt) Ltd logo
Champion
Panamax Inc. logo
Philippine Long Distance Telephone Company (PLDT) logo
Champion
SMART COMMUNICATIONS, INC. logo
Champion
Sri Lanka Telecom PLC logo
Champion
Tech Mahindra Limited logo
TechNarts (Nart Bilişim) logo
TM Technology Services Sdn Bhd logo
Champion
Turknet logo
Champion
Waylay logo

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