The Focus Group-AI Native Networking (AINN) Build-a-thon 2025 concluded today with the successful presentation of innovative, AI-native telecom solutions by 10 finalist teams from around the world. Organized as part of the 3rd Meeting of ITU Focus Group on Autonomous Networks (FG-AINN) held in New Delhi from 11th June 2025, the event brought forward key contributions towards standardization in future autonomous networks.

Launched jointly by the Telecommunication Engineering Centre (TEC), the technical arm of the Department of Telecommunications (DoT), and the International Telecommunication Union (ITU), the Build-a-thon served as a global innovation platform aligned with FG-AINN’s objectives.

This global innovation challenge aimed to accelerate the development of AI-native networking systems, contributing to international standardization efforts by identifying key gaps, proposing use cases, developing architectural frameworks, and building Proofs of Concept (PoCs). The Build-a-thon served as a collaborative platform for developers, researchers, students, startups, and telecom professionals to create open-source solutions for autonomous networks, including closed-loop automation, intent-based operations, and digital twin ecosystems.

The FG-AINN Build-a-thon 2025, a crowdsourced coding event brought together experts from academia, industry, and startups to co-create practical demonstrations of AI-native concepts through interactive mentoring and collaborative sessions. The registration for the event began in early May 2025, followed by regular mentoring sessions. A total of 23 teams comprising 57 participants from around the world registered, out of which 10 teams were shortlisted for the final presentation today.

All shortlisted participants were felicitated with certificates and the top three prizes were awarded to Team SliceMinds (1st place), Team SNR (2nd place), and Team Nowiresattached (3rd place). Special recognition was given to Team AIONETx as the best all-women’s team, and Teams OMACS and SSN for excellence in mentorship.

The awards were presented by Smt. Tripti Saxena (Sr. DDG, TEC), Dr. Rajkumar Upadhyay (CEO, C-DOT), and Shri Deepesh Srivastava (AVP, Tejas Networks).

 

 

Key outcomes of the event included:

· Practical AI-driven solutions for network slicing, traffic shaping, intent-based automation, and self-healing networks;

· Development of PoCs for digital twins, LLM-based knowledge platforms, and RAN optimization;

· Strong engagement of academia, startups, and professionals through structured mentoring and hands-on demonstrations.

This Build-a-thon marks a significant step towards India’s and ITU’s shared goal of fostering ethical, inclusive, and globally standardized AI to power digital transformation and sustainable telecom innovation.

This is an important initiative by TEC and ITU-T FG-AINN as part of country’s continued commitment to promote standardized, ethical, and inclusive AI that advances digital transformation and sustainable development.

About finalist teams demonstrated diverse approaches:

1. AIONETx A women-led team from VIT Chennai focused on packet classification and dynamic policy injection using AI inference for traffic shaping, exploring adaptive control in live networks.
2. Sliceminds Students and faculty from SRM Institute of Science & Technology tackled intelligent network slicing through JSON-based vendor selection, agent-based monitoring, and 5G function mapping, using an Open5GS lab setup.
3. SNR A team from RVCE Bengaluru demonstrated intent-based automation, converting human operator input into CLI commands using AI-driven models, integrating operator intent with direct network actions.
4. Nowiresattached Students from MIT Bengaluru worked on self-healing networks using fault injection in ns3, and employed LLM agents integrated with OpenAI’s MCP tools for autonomous fault resolution.
5. Cellucast Comprising members from RVCE and Nokia, presented dynamic AI model selection for traffic analysis and RAN parameter optimization, exploring data handling mechanisms for scalable operations.
6. Sigvision A joint effort by IIIT-Bangalore and Nokia proposed human activity detection using wireless signals with bi-directional LSTM models, focusing on cross-layer AI application integration.
7. SSN From SSN College of Engineering, Chennai enabled AI-driven beamforming simulations, linking simulation intent to YAML-based configuration and automation, for smarter RF planning.
8. SPV Software engineers and mentors from SRM University (AP) applied AI for fake news detection within the network, exploring federated learning, CDN-layer inference, and semantic verification as network-integrated services.
9. OMACS Students from SRM University, Guntur showcased health monitoring over 5G, proposing cross-domain data sharing, AI pipeline deployment under low-latency constraints, and app-to-network interface design.
10. TechRanger developed a Large Language Model (LLM)-driven knowledge base referencing ITU specifications, aimed at generalizing telecom standards into intelligent, reusable assets.

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