Spotlight on Tech

Rakuten Symphony’s Top 25 AI initiatives: Software development life cycle

By
Dewa Siswanto
Senior Director of Product Operations, OSS
Rakuten Symphony
August 21, 2025
5
minute read

Rakuten Symphony has developed a prioritized list of the top 25 AI initiatives for communications service providers, divided into five categories. The Rakuten Symphony AI-based software development life cycle (AI-SDLC) tool is ranked level three out of five in priority. It provides automation of SDLC workflow tasks based on AI analysis.

With the growing popularity of Open RAN, telco cloud and virtualization initiatives in telecom networks, service providers have an increasing need to manage software development life cycles (SDLC) for a wide range of network functions. Rakuten Symphony’s AI-based SDLC software (AI-SDLC) is a chat-based generative AI module that helps users perform the full range of SDLC tasks.

The tool can be used by product managers, business analysts, user interface/experience designers, software developers, quality assurance and release managers who contribute to the SDLC process. Some key tasks covered by the tool include:  

  • Assisting product managers and business analysts in conducting market research, brainstorming new features, and performing competitive analysis. This input is used to create natural language feature descriptions that make up the user story for the software engineering team.
  • Enabling UI/UX designers to create wireframes and designs based on the user story requirements using the AI-SDLC.
  • Supporting developers in code generation, debugging and code review. The AI agent can also assist the QA team with test case generation.
  • Using details from data stored in the AI-SDLC can be used to create release notes and documents needed for product launch, thus covering the final stages of the SDLC.
  • Helping to ensure that new features are aligned with O-RAN Alliance and 3GPP standards.

AI-SDLC benefits

The benefits of the software include immediate feedback and automation at every stage of the process, which improves process accuracy and efficiency. The software reduces the time and cost of SDLC by providing real-time responses to data inputs, immediately notifying team members of errors and correcting them. With this AI tool, there is greater process consistency due to 95% accuracy in generating SDLC artifacts for engineering, as well as a 40% increase in process efficiency when using the tool.  

Real-world data for accurate model training

The AI-SDLC tool was developed using the Rakuten AI for Telecom Platform, which provided the development team with real-world log data from actual users using production network systems. The platform includes the necessary data and domain knowledge to ensure the application adheres to industry standards such as 3GPP and O-RAN specifications. Additionally, the platform offers dataset training to ensure the accuracy of the tool’s results at each stage of the life cycle.  

Conclusion

With the services of so many subscribers depending on increasingly complex software stacks, ensuring the SDLC is efficient and accurate is critical. The AI-SDLC tool is an ideal application of a telecom AI model that leverages real-world data and brings insights to every stage of the SDLC process – from software conception to release notes and documentation.  

With interfaces for every team member involved in the process—from product management to quality assurance—the work completed at each development stage is accessible at the next, streamlining the overall development process. The AI-SDLC tool is essential for ensuring that software meets users' needs.

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