Author
Listed:
- Amar Gurajapu
(Principal Member of Tech Staff, Network Systems, AT&T, New Jersey, United States)
- Swapna Anumolu
(Principal Member of Tech Staff, Network Systems, AT&T, New Jersey, United States)
- Vardhan Garimella
(Consultant, Intellibus, United States)
- Venkata Manikanta Sai Ramakrishna Chundi
(Lead Architect, Intellibus, United States)
- Venkata Sita Anand Prakash Gubbala
(Vice President, Wissen Inc, United States)
Abstract
The evolution from isolated OSS/BSS processes to fully automated digital service factories marks a significant advancement in telecom operations. While Lifecycle Service Orchestration (LSO) traditionally centers on connectivity, Digital Service Factories broaden this scope to encompass the entire service lifecycle including provisioning, scaling, policy enforcement, assurance, billing, and customer experience management. In this paper, we introduce DSF-AI, an AI-powered service factory framework designed to translate business intent into actionable workflows, enforce policies as code, and orchestrate network and cloud resources seamlessly across on-premises infrastructure, Azure, and AWS. Leveraging reinforcement learning for ongoing service optimization, pilot migration demonstrated substantial benefits where service activation times improved by 60% (from 4.8 hours to 1.9 hours), manual handoffs per incident were reduced by half, SLA compliance reached 98.5% over 30 days, and policy violations decreased by 70% compared to legacy CI/CD approaches. This paper outlines DSF-AI’s layered architecture, details its AI-driven orchestration engine, visualizes data flows and process sequences, and provides a quantitative assessment along with practical insights for transformation leaders.
Suggested Citation
Amar Gurajapu & Swapna Anumolu & Vardhan Garimella & Venkata Manikanta Sai Ramakrishna Chundi & Venkata Sita Anand Prakash Gubbala, 2025.
"Digital Service Factories: AI-Driven Lifecycle Service Orchestration Beyond Connectivity,"
Journal of Computer Science and Technology Studies, Al-Kindi Center for Research and Development, vol. 7(6), pages 1115-1119, June.
Handle:
RePEc:alk:jcsts0:v:7:y:2025:i:6:id:12113
DOI: 10.32996/jcsts.2025.7.6.133
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