The Ministry of Communications' FGAINN Buildathon 2025, a global innovation challenge focused on AInative networking, concluded in New Delhi. Organized by the Telecommunication Engineering Centre (TEC) and the International Telecommunication Union (ITU), the Buildathon aimed to accelerate the development and standardization of AInative networking systems. Ten finalist teams from around the world presented innovative telecom solutions, with Team SliceMinds winning the top prize. The event facilitated collaboration among developers, researchers, students, startups, and telecom professionals to create open-source solutions for autonomous networks. Key outcomes included practical AIdriven solutions for network slicing, intentbased automation, and selfhealing networks. The Buildathon marks a significant step towards fostering ethical, inclusive, and globally standardized AI for digital transformation and sustainable telecom innovation.
Key Entities Referenced
Ministry of Communications: The government ministry overseeing the FGAINN Buildathon 2025.
FGAINN Buildathon 2025: A global innovation challenge focused on AInative telecom solutions, organized as part of the ITU Focus Group on Autonomous Networks.
SliceMinds: The team that won first place at the AINative Networking Buildathon.
IndiaITU: A collaboration between India and the International Telecommunication Union (ITU) to promote AI in telecom.
PIB Delhi: Press Information Bureau, Delhi, the source of the notification.
Focus GroupAI Native Networking AINN: An ITU focus group related to autonomous networks and AI.
New Delhi: The city where the 3rd Meeting of ITU Focus Group on Autonomous Networks FGAINN was held.
11th June 2025: The start date of the ITU Focus Group on Autonomous Networks FGAINN meeting in New Delhi.
Telecommunication Engineering Centre TEC: The technical arm of the Department of Telecommunications (DoT).
Department of Telecommunications DoT: A government department involved in the Buildathon.
International Telecommunication Union ITU: An international organization involved in the Buildathon and standardization efforts.
Proofs of Concept PoCs: A deliverable from the Buildathon, intended to show practical applications of AInative networking systems
Team SNR: The team that won second place at the AINative Networking Buildathon.
Team Nowiresattached: The team that won third place at the AINative Networking Buildathon.
Team AIONETx: The best all-womens team at the AINative Networking Buildathon.
Teams OMACS and SSN: Teams recognized for excellence in mentorship at the AINative Networking Buildathon.
Smt. Tripti Saxena Sr. DDG: A person who presented awards at the AINative Networking Buildathon, affiliated with TEC.
Dr. Rajkumar Upadhyay CEO: A person who presented awards at the AINative Networking Buildathon, affiliated with C DOT.
Shri Deepesh Srivastava AVP: A person who presented awards at the AINative Networking Buildathon, affiliated with Tejas Networks.
VIT Chennai: Institution affiliated with team AIONETx.
SRM Institute of Science Technology: Institution affiliated with team Sliceminds.
Open5GS: Lab setup used by team Sliceminds
RVCE Bengaluru: Institution affiliated with team SNR and Cellucast.
MIT Bengaluru: Institution affiliated with team Nowiresattached.
Nokia: Company affiliated with team Cellucast and Sigvision.
IIITBangalore: Institution affiliated with team Sigvision.
SSN College of Engineering, Chennai: Institution affiliated with team SSN.
SRM University AP: Institution affiliated with team SPV.
SRM University, Guntur: Institution affiliated with team OMACS.
Large Language Model LLM: Technology used by team TechRanger.
OpenAI: Company whose tools were used by Nowiresattached
MCP: OpenAI's MCP tools were used by Nowiresattached
TechRanger: Team that developed a Large Language Model LLMdriven knowledge base referencing ITU specifications
Ministry of Communications
FG-AINN Build-a-thon 2025 Concludes with Global
Show of AI-Native Network Innovation
Team SliceMinds Wins Top Honors at AI-Native
Networking Build-a-thon
Build-a-thon Marks Milestone in India–ITU Efforts to
Foster Ethical, Inclusive, and Standardized AI for
Telecom Innovation
Posted On: 13 JUN 2025 8:06PM by PIB Delhi
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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