Data & AI Collaboration Frameworks enabling secure multi-operator federated learning to train Network Language Models (NLMs).
The PG accelerates scalable AI adoption in telecom by tackling data access, cross-company silos, trust/security, and increasing network complexity, while preparing the ecosystem for AI-native 6G by design.
Domains We Cover
These domains represent the full telecom network stack, ensuring that AI frameworks developed by the Project Group can operate across end-to-end environments, rather than within isolated silos.
RAN (Radio Access Network)
The Project Group supports AI innovation in the RAN by enabling secure, collaborative data frameworks that improve how operators design, deploy, and optimize radio networks. This includes using federated learning and domain-specific AI models to enhance coverage planning, energy efficiency, interference management, and real-time performance optimization across multi-vendor environments.
IP Transport Networks
For transport networks, the PG focuses on applying AI to improve traffic engineering, resilience, and operational automation. By enabling shared data models and trusted collaboration across operators, the group helps develop AI solutions that can predict congestion, optimize routing decisions, and strengthen network reliability at scale.
Fixed Access (Including WiFi)
Within fixed and WiFi networks, the PG helps create AI frameworks that improve user experience, service quality, and operational efficiency. This includes enabling cross-domain insights for network performance, supporting proactive fault detection, and developing AI tools that optimize broadband access in increasingly complex, hybrid network environments.
Core Networks
In the core domain, the PG advances AI-driven automation for service orchestration, network management, and lifecycle operations. By supporting secure data collaboration and domain-specific AI models, the group enables operators to improve network intelligence, streamline operations, and support emerging AI-native service architectures.
Key Scope Pillars
The Project Group focuses on six core areas to accelerate secure, scalable AI adoption across telecom networks.
Federated AI Collaboration
Developing privacy-preserving frameworks that allow operators and ecosystem partners to securely collaborate on data and jointly train AI models without exposing sensitive information.
Network Language Models & AI Agents
Creating domain-specific AI models and intelligent agents designed to understand telecom environments and support real-world operator use cases.
Cross-Domain Data & AI Framework
Designing a unified architecture that enables AI to operate seamlessly across RAN, transport, fixed access, and core network domains.
AI Customization & Best Practices
Defining practical guidelines for adapting AI models to telecom environments, including tuning, deployment workflows, and operational integration.
Validation, Benchmarking & Readiness
Establishing testing methods, performance benchmarks, and validation processes to ensure AI solutions are interoperable, trustworthy, and production-ready.
Ecosystem Alignment & Collaboration
Working horizontally across TIP project groups and industry organizations to harmonize standards, frameworks, and interoperability approaches.
Announced at MWC26: Data & AI Foundations
On March 4, 2026 at MWC26 in Barcelona, we announced the launch of the Data & AI Foundations Project Group. This new industry initiative focuses on building the data architecture, AI frameworks, and collaborative foundations needed to support the next generation of AI-native telecom networks.
Learn more in our press release.
Our Target Deliverables
Federated Learning Architectures
Privacy-preserving, multi-organization training of telecom NLMs
Telecom Domain Model Customization Techniques & Best Practices
Guidance to adapt foundation NLMs to RAN, Transport, Fixed, Core use cases
Benchmarking & Validations
Standardized procedures/metrics/test environments to evaluate performance, robustness, deployment readiness
Test Plans & Allocation Criteria
(for agents/apps, where relevant)
Developed in collaboration with other PGs
OpenLAN Subgroup Leadership
TIP OpenWiFi is the first project developed and contributed by the OpenLAN community. OpenWiFi is a community-developed, disaggregated Wi-Fi software system, offered as free open-source software, that includes both a cloud controller SDK and an Enterprise-grade Access Point (AP) firmware, designed and validated to work seamlessly together.
Subgroup Leadership
Jaspreet Sachdev (Kinara Systems)
Marcel Chenier (NetExperience,
a Pavlov Media company)
Sachin Mehra
(Inventum)
OpenLAN Switching (OLS)
OpenLAN Switching is building on the foundation of OpenWiFi, to expand the project to provide a unified solution for LAN switches that has all the same attributes as OpenWiFi (open-source, multi-vendor, interoperable whitebox, hardened and validated E2E systems).
Subgroup Leadership
Binny Jeshan
(Truminds Software Systems)
Teng Tai Hsu
(Edgecore)
OpenLAN Gateway (OLG)
OpenLAN Gateway (OLG) completes the OpenLAN mission of building a unified solution for in-building networks (WLAN, LAN, WAN), OLG focuses on the on-prem routing, security & compute capabilities. This is an open-source project, supporting multi-vendor (SoC/ODM), with an interoperable Cloud Management protocol and validated E2E systems.
Subgroup Leadership
Doron Givoni
(Shasta Cloud)
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