Strengthening Network Operations Knowledge-Base through Locally-Hosted Generative AI
+LLMNetOps is an ISIF Asia 2025 project by Universitas Brawijaya aimed at addressing the AI-literacy gap among network operations professionals in IDREN (Indonesia Research and Education Network) member institutions.
+Many IDREN member institutions struggle to adopt AI-supported network management due to limited staff, uneven expertise, and reliance on undocumented knowledge. Generative AI offers potential for improving documentation and troubleshooting, but most administrators lack training, confidence, and tools that respect data privacyβcreating an AI-literacy gap.
+This project aims to address this gap by building foundational AI knowledge, fostering peer collaboration, and promoting locally-hosted open-source LLM models as privacy-aware solutions tailored to institutional needs in network operations.
+Understanding the AI adoption barriers in network operations
+Many institutions operate with small IT teams who lack bandwidth to explore and implement new technologies like AI.
+Technical knowledge varies significantly across institutions, creating disparities in AI adoption readiness.
+Critical operational knowledge often exists only in the minds of experienced staff, making AI-assisted documentation crucial.
+Institutions are rightly concerned about sending sensitive network data to cloud-based AI services.
+Most administrators have not received formal training on AI technologies and their practical applications.
+Without hands-on experience, staff lack confidence to evaluate and adopt AI solutions.
+How LLMNetOps aligns with ISIF Asia's strategic themes
+Training and empowering network professionals with AI literacy and practical skills for implementing privacy-aware LLM solutions.
+Introducing contextual AI applications for infrastructure operationsβmoving beyond general productivity to specialized technical support.
+Enabling institutional transformation through privacy-first AI adoption that respects data sovereignty and institutional autonomy.
+Four key themes driving our approach
+We promote locally-hosted open-source LLM models as a practical solution for institutions concerned about data privacy and institutional autonomyβan issue often overlooked in AI adoption discussions.
+We introduce the use of generative AI not for general productivity, but specifically to support technical teams in managing, understanding, and documenting their own infrastructure.
+We focus on empowering network and IT staff with the knowledge and confidence to use AI in their daily tasks, addressing the training and tool gaps that prevent AI adoption.
+Through workshops and peer collaboration, we encourage a culture of learning and shared problem-solving, rather than one-off training sessions.
+Supported by leading organizations in the Asia-Pacific region
+LLMNetOps is funded by the APNIC Foundation through the ISIF Asia 2025 grant program. The project is implemented by Universitas Brawijaya, Indonesia, in collaboration with IDREN member institutions.
+Join us in building privacy-first AI capabilities for network operations
+Get in touch with the LLMNetOps team
+We'd love to hear from you
+ + + +Learn more about our partners and funders
+ +The APNIC Foundation is a not-for-profit organization focused on enabling a global, open, and secure Internet for the Asia Pacific region.
+ Visit Website β +The Information Society Innovation Fund (ISIF Asia) supports projects that develop solutions to ICT-related issues in the Asia Pacific region.
+ Visit Website β +Indonesia Research and Education Network connects academic and research institutions across Indonesia for collaboration and knowledge sharing.
+ Visit Website β +One of Indonesia's leading public universities, implementing the LLMNetOps project to advance AI adoption in network operations.
+ Visit Website β +Track our progress across four key deliverable areas
+Initial survey, curriculum design, and prototyping platform for locally-hosted LLM training materials.
+ +| Activity | +Target | +Status | +
|---|---|---|
| Initial Needs Assessment Survey | +1 report | +Not Started | +
| Curriculum Design and Development | +1 curriculum | +Not Started | +
| Module Development (5 modules) | +5 modules | +Not Started | +
| Platform Prototyping | +1 prototype | +Not Started | +
| Pilot Feedback Collection | +1 report | +Not Started | +
| Developing a Webpage Portal | +1 website | +In Progress | +
Two hands-on workshop sessions focusing on LLM fundamentals and AI agentic workflows for network operations.
+ +| Activity | +Target | +Status | +
|---|---|---|
| Workshop Planning | +Complete planning | +Not Started | +
| Workshop Session 1: LLM Fundamentals | +1 session | +Not Started | +
| Workshop Session 2: AI Agentic Workflow | +1 session | +Not Started | +
| Workshop Documentary | +Complete documentation | +Not Started | +
Comprehensive survey, case studies, and whitepaper development to document project impact.
+ +| Activity | +Target | +Status | +
|---|---|---|
| Final Survey & Data Collection | +1 survey report | +Not Started | +
| Case Brief & Testimonial Collection | +3+ case studies | +Not Started | +
| Whitepaper on NetOps with AI | +1 whitepaper | +Not Started | +
Project reporting and dissemination of findings to stakeholders and funding organization.
+ +| Activity | +Target | +Status | +
|---|---|---|
| Midterm Reporting | +1 midterm report | +Not Started | +
| Final Report Writing & Dissemination | +1 final report | +Not Started | +
Curriculum Development (33%)
+Workshop Delivery (60%)
+Survey & Analysis (3%)
+Reporting (3%)
+Building foundational AI knowledge through locally-hosted open-source LLMs, fostering peer collaboration, and empowering IDREN member institutions with privacy-aware solutions for network operations.
+Bridging the AI Literacy Gap in Network Operations
+Many IDREN member institutions struggle to adopt AI-supported network management due to limited staff, uneven expertise, and reliance on undocumented knowledge. Generative AI offers potential for improving documentation and troubleshooting, but most administrators lack training, confidence, and tools that respect data privacyβcreating an AI-literacy gap.
+LLMNetOps aims to address this gap by building foundational AI knowledge, fostering peer collaboration, and promoting locally-hosted open-source LLM models as privacy-aware solutions tailored to institutional needs in network operations.
+Our strategic approach to AI-enabled network operations
+Developing AI literacy and technical skills among network operations professionals through structured training and hands-on workshops.
+Introducing contextual AI applications specifically designed for infrastructure operations, documentation, and troubleshooting.
+Enabling IDREN institutions to confidently adopt privacy-first AI solutions that align with their specific requirements.
+Empowering institutions with privacy-first AI solutions
+Promote locally-hosted open-source LLM models as a practical solution for institutions concerned about data privacy and institutional autonomy.
+Introduce the use of generative AI specifically to support technical teams in managing, understanding, and documenting their own infrastructure.
+Empower network and IT staff with the knowledge and confidence to use AI in their daily tasks.
+Build a culture of learning and shared problem-solving through workshops and peer collaboration.
+Investigate how locally-hosted LLMs can be safely integrated into network operations while ensuring data security.
+Empower IDREN members to confidently assess and adopt AI solutions that align with their specific requirements.
+Interested in LLMNetOps? Join our upcoming workshops or connect with us!
+Training modules, case studies, and documentation for privacy-aware AI deployment
+Comprehensive curriculum on locally-hosted LLMs for network operations
+ +Comprehensive introduction to LLMs covering architecture, capabilities, and applications in network operations.
+ +Deep dive into privacy considerations, data protection, and institutional autonomy in AI deployment.
+ +Practical guide to building Retrieval-Augmented Generation pipelines for network documentation and troubleshooting.
+ +Advanced module on building AI agents for automated network operations tasks.
+ +Guide to integrating locally-hosted LLMs with existing network infrastructure and monitoring systems.
+ +Research outputs and policy insights
+ +Survey results and analysis of AI adoption challenges across IDREN member institutions.
+ +Comprehensive whitepaper on AI adoption policies and recommendations for network operations in educational institutions.
+ +Real-world implementation examples from IDREN institutions
+ +Are you implementing locally-hosted LLMs in your institution? We welcome case study contributions from IDREN member institutions. Your experience could help others on their AI adoption journey.
+ Contact Us to Contribute +Recommended resources for learning about LLMs and AI deployment
+ +Run large language models locally. An easy way to get started with locally-hosted LLMs.
+ Visit Website β +The AI community building the future. Access thousands of open-source models and datasets.
+ Visit Website β +Build applications with LLMs through composability. Framework for RAG pipelines and AI agents.
+ Visit Website β +Latest news and insights from the Asia-Pacific networking community.
+ Visit Website β +Questions about resources or looking for specific materials?
+Hands-on Training on Privacy-Aware LLM Deployment for Network Operations
+Two comprehensive sessions designed for network operations professionals
+ + +Introduction to Large Language Models and Privacy-Aware AI
+This foundational session introduces participants to Large Language Models, covering core concepts, privacy considerations, and the fundamentals of local deployment. Participants will learn why locally-hosted LLMs are crucial for institutional data privacy.
+ +Practical Implementation and Hands-on Exercises
+Building on Session 1, this advanced session focuses on practical implementation of AI agentic workflows for network operations. Participants will work with live prototypes and learn to integrate LLMs into their network management workflows.
+ +Network operations professionals, IT administrators, and technical staff from IDREN member institutions. Open to other educational and research institutions in Indonesia.
+The workshops are free of charge, funded by APNIC Foundation through the ISIF Asia 2025 grant program.
+Instruction will be primarily in Indonesian with materials available in both Indonesian and English. English support available.
+Participants who complete both sessions will receive a certificate of completion from Universitas Brawijaya.
+Common questions about our workshops
+ +The workshops are primarily designed for network operations professionals, IT administrators, and technical staff from IDREN member institutions. However, we welcome participants from other educational and research institutions in Indonesia who are interested in privacy-aware AI deployment.
+No, the workshops are free of charge. This project is funded by APNIC Foundation through the ISIF Asia 2025 grant program.
+Participants should have a laptop with at least 8GB RAM. For hands-on exercises, we'll provide access to cloud-based environments. Specific setup instructions will be shared before each workshop.
+Yes, all workshop materials including slides, recordings (when available), and hands-on guides will be made available through our Resources page. Materials are provided in both Indonesian and English.
+Instruction will be primarily in Indonesian with materials available in both Indonesian and English. English support will be available for non-Indonesian speakers.
+No prior AI or machine learning experience is required for Session 1. Basic familiarity with networking concepts and command-line interfaces is helpful. Session 2 builds on Session 1 content.
+Be the first to know when registration opens
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