Ericsson has launched Agentic rApp as a Service (rApp aaS) on Amazon Web Services, positioning the new offering as a catalyst for communications service providers (CSPs) aiming to accelerate their transition towards fully autonomous networks.
The new rApp aaS model allows CSPs to deploy radio access network applications (rApps) through AWS Marketplace, reducing deployment friction while improving scalability, flexibility and cost control. Built on AWS, the service introduces agentic AI for reasoning and coordination of network optimisation workflows, alongside generative AI capabilities that allow operators to interact with the network using natural language.
According to Ericsson, the solution is designed to support CSPs on the path to Level 4 network autonomy, where networks can make and execute decisions with minimal human intervention. By translating natural language prompts into machine-executable instructions, the agentic AI system enables operations teams to “talk” to the network, simplifying complex optimisation tasks.
The service is based on an open Service Management and Orchestration (SMO) architecture and connects to the Non-RT RIC within the SMO framework via the R1 interface defined by the Open RAN Alliance. Ericsson said this ensures interoperability and alignment with the wider Open RAN innovation ecosystem.
Field trials of rApp aaS are already underway with several global CSPs. Vivo Brazil is among the first to test the solution in a live environment. Elmo Matos, Director of Mobile Network Core and Deployment at Vivo, said the collaboration is enabling the operator to explore practical applications of AI at scale. “Collaborating with Ericsson on this initiative allows us to test different applications of artificial intelligence aimed at enhancing network experience. With AWS support, we will explore the rApp aaS model and expand AI-driven functionalities, focusing on improving network capacity and automation on a national scale,” he said.
From AWS’s perspective, the launch highlights the growing role of cloud-native platforms in telecom modernisation. Fabio Cerone, Managing Director for the EMEA Telco business unit at AWS, described the announcement as a turning point for the industry. “Ericsson’s launch of Agentic rApp as a Service represents a major milestone in the telecom industry, combining Ericsson’s proven telecom leadership with AWS leading cloud and AI capabilities. This as-a-Service model transforms how communications service providers can consume network automation expertise on-demand through AWS,” he said, adding that the model allows CSPs to focus more resources on customer experience while accelerating their autonomy journey.
Industry analysts see the move as distinctive in a crowded rApp market. James Crawshaw, Practice Leader at Omdia, said that while many vendors claim to offer rApps, few have demonstrated production-grade deployments using ORAN-compliant interfaces. “No other vendor offers a comparable rApp-as-a-Service solution. These two aspects create a real distinction, setting this new offering apart,” he noted.
Ericsson said the launch builds on its long-standing work in AI-driven network optimisation. The company’s existing AI solutions currently handle more than 100 million AI inferences each day across 11 million cells, serving over two billion subscribers worldwide. By combining this experience with AWS’s cloud infrastructure and elastic consumption model, rApp aaS allows CSPs to benefit from advanced rApps without heavy upfront capital investment.
Jean-Christophe Laneri, Head of Cognitive Network Solutions at Ericsson, said the offering reflects the company’s broader autonomous networks strategy. “Our Agentic rApp as a Service represents a significant milestone in our vision for autonomous networks. By harnessing Agentic AI and AWS capabilities, we reduce operational complexity and empower CSPs to focus on delivering enhanced network experiences,” he said.
Ericsson plans to showcase the new rApp aaS at Mobile World Congress 2026 in Barcelona, where it will demonstrate the agentic AI capabilities running on AWS and outline how the model can support large-scale CSP transformation towards autonomous operations.