peterindia.netTelecom AI Platforms
Platforms for AI in telecom: AI-RAN and network AI, BSS/OSS and customer AI, cloud and foundation platforms, and the open models and standards that make AI-native networks interoperable.
Accelerated computing, Aerial AI-RAN, and in 2026 an open telco reasoning model on Nemotron 3 with agentic blueprints for network configuration and RAN energy efficiency, released through the GSMA Open Telco AI initiative.
Best for: AI-RAN and autonomous-network AI built on GPUs.
Visit NVIDIA for Telecommunications →Nokia advances AI-RAN toward commercial deployment and announced in October 2026 a sovereign agentic AI platform for telco autonomy developed with NVIDIA.
Best for: Sovereign, multi-domain network autonomy.
Visit Nokia →Offers AI in its RAN and network software, including an Agentic rApp as a Service on AWS for cloud-native RAN optimization.
Best for: RAN optimization with rApps and agentic AI.
Visit Ericsson →Promotes autonomous network (L4) capabilities and AI-enabled radio, transport and core products; its equipment is restricted in some markets, so check local rules.
Best for: Autonomous network operations where permitted.
Visit Huawei →Virtualized and Open RAN with AI-driven automation, radios and 5G core for operators.
Best for: Virtualized RAN with AI-driven operations.
Visit Samsung Networks →SoftBank's converged AI-RAN platform that runs RAN software and edge AI applications together on shared accelerated infrastructure.
Best for: Converged AI and RAN workloads.
Visit SoftBank AITRAS →Telco-specific AI platform from Amdocs that supports multiple LLMs and agentic experiences across billing, care and operations, exposed through REST, MCP and A2A protocols.
Best for: Agentic AI embedded in BSS and operations.
Visit Amdocs amAIz →Network and operations software vendor that introduced a GenAI Telco Solution for use-case innovation across OSS/BSS.
Best for: GenAI use cases across OSS/BSS.
Visit Netcracker →Industry CRM for operators with AI agents (Agentforce) for customer engagement, quote-to-order and service.
Best for: AI agents in customer-facing operations.
Visit Salesforce Communications Cloud →Cloud charging and the BSS Magic AI layer with an ontology for connecting BSS data, built on AWS.
Best for: Modernizing BSS with AI and an ontology.
Visit Totogi →Network planning, optimization and assurance vendor that introduced VistAI, an agentic framework of intent-based AI agents.
Best for: Agentic network planning and assurance.
Visit Infovista →AWS services and partner solutions for operators, including AI, cloud RAN and core, used by vendors such as Ericsson.
Best for: Cloud-hosted network and AI workloads.
Visit AWS for Telecommunications →Google Cloud's solutions for operators, including AI and data analytics for network, customer and operations use cases.
Best for: Data and AI platforms for operators.
Visit Google Cloud for Telecommunications →Microsoft's industry solutions for operators, with Azure AI and Foundry reported as an agentic AI blueprint for several large operators.
Best for: Azure AI and agentic blueprints for telcos.
Visit Microsoft for Telecommunications →GSMA initiative for open datasets, benchmarks and models for AI in telecom, including the NVIDIA telco model.
Best for: Shared open telco AI resources.
Visit GSMA Open Telco AI →Industry association whose Open APIs and Open Digital Architecture underpin interoperable OSS/BSS and AI agents.
Best for: Standards for AI-native OSS/BSS.
Visit TM Forum →Defines the open RAN interfaces and the RIC with xApps and rApps that run AI-driven RAN optimization.
Best for: Open interfaces for RAN AI.
Visit O-RAN Alliance →Match your use case to a starting point, then compare platforms.
| RAN energy savings and AI-RAN | NVIDIA, Nokia, Ericsson, Samsung, SoftBank AITRAS |
|---|---|
| Autonomous network operations (NOC automation) | Nokia and NVIDIA agentic platform, Huawei, Infovista, Amdocs |
| Customer care and sales agents | Salesforce Communications Cloud, Amdocs amAIz, Totogi |
| BSS modernization with AI | Totogi BSS Magic, Netcracker, Amdocs |
| Cloud-hosted AI and data | AWS, Google Cloud and Microsoft for telecommunications |
| Open models, datasets and standards | GSMA Open Telco AI, TM Forum, O-RAN Alliance |
Neighbouring directories and hubs.
Quick answers.
A telecom AI platform is software and infrastructure that lets operators build and run AI for networks, customers and operations: models and agents trained or tuned on telecom data, plus the compute, data and governance around them.
AI-RAN runs AI and radio access network workloads on the same accelerated computing platform, so the network can carry traffic and host edge AI. NVIDIA, Nokia, SoftBank, T-Mobile and others are developing and trialling it.
Autonomous networks use AI to plan, configure, optimize and repair themselves with little human input, often described in levels up to L4. Agentic AI adds goal-driven agents that carry out multi-step tasks across network and business systems.
General language models lack telecom knowledge such as standards, network logs and alarms. Telco models, for example NVIDIA's open Nemotron-based model released through the GSMA Open Telco AI initiative, are tuned on that data to reason about network operations.
Start from the use case, whether RAN energy savings, NOC automation or customer care, then compare data sovereignty, open interfaces such as TM Forum Open APIs and O-RAN, integration with existing OSS/BSS, governance and controls, and total cost.
Descriptions summarise vendor announcements and trade-press reports, checked on 12 November 2026. Ericsson, GSMA, TM Forum and Totogi return 403, and Netcracker and Microsoft return no response, to automated checks and may need a manual click. Many capabilities are announced, in trial or early deployment, and Huawei equipment is restricted in some markets, so confirm details and local rules before relying on them.