How Our Claude Developers Built Conversational Telecom Operations for Rakuten Symphony

TL;DR: Claude developers for telecom operations shipped Rakuten Symphony a unified Gen AI intelligence platform on Claude via Amazon Bedrock in 12 weeks. It handles multi-domain telecom queries, geospatial network analytics, predictive maintenance, and closed-loop automation across network operations, site management, project intelligence, and RAN optimisation. Outcomes: 85% reduction in inspection time, 60% faster root cause analysis, 3× faster new-site decision-making, and $2.4M+ in projected year-1 savings.

Rakuten Symphony is a global telecom technology platform, transforming telecom operations through AI, automation, cloud-native infrastructure, and predictive intelligence. It manages large-scale telecom workflows spanning network operations, site management, project intelligence, and RAN optimisation.

Even with strong existing platforms, one thing was missing: a unified conversational layer that could reason across domains, predict issues before they surfaced, and orchestrate operational decisions end to end. That is what we built.

The Problem

Rakuten's operational stack was full of capable systems that did not talk to each other.

• Network operations, site qualification, project forecasting, and installation audits each ran on their own tooling.
• Workflows across those domains were manual and reactive.
• There was no predictive intelligence layer — issues got resolved after they surfaced, not before.
• No conversational AI. No intelligent orchestration. No real-time recommendation engine.

Multi-domain telecom analysis was hard. Proactive network optimisation was harder. Automated risk forecasting was mostly aspirational.

The result: operational delays, slower decision-making, inefficient resource allocation, and a hard ceiling on how much the ops team could scale.

The Solution

Our Claude developers built a unified Gen AI telecom intelligence ecosystem — conversational AI, predictive analytics, intelligent orchestration, and workflow automation, all in one operational layer. Claude on Amazon Bedrock handles the reasoning and multi-domain query interpretation, orchestrated through LangGraph.

Conversational AI and Context Management

• Multi-domain telecom queries handled in one interface
• Operational intent interpreted correctly across domains
• Context maintained across long operational workflows
• Predictive recommendations without restarting each analysis
• Smooth conversational operational intelligence experience

Geospatial and Predictive Intelligence

• Geospatial network heatmap analytics
• Traffic forecasting for planned events
• Subscriber experience analysis
• AI-driven root cause analysis
• Predictive maintenance recommendations
• Dependency and resource impact simulations
• Real-time anomaly detection

Workflow Orchestration and Ranking

• Federated telecom operational databases
• Apache Spark analytics pipelines
• Milvus and ChromaDB vector databases
• Kafka real-time streaming
• LangGraph orchestration frameworks
• FastAPI AI microservices
• Redis and RabbitMQ messaging

Interactive Operational Intelligence

• Conversational telecom analytics
• Interactive geospatial network visualisation
• Real-time AI recommendations
• Operational simulation and forecasting
• Automated workflow orchestration
• Closed-loop operational automation
• Seamless flow between AI recommendations, analytics, and operations

The Architecture

Infrastructure and Deployment

• Claude on Amazon Bedrock for reasoning and multi-domain analysis
• LangGraph and FastAPI for orchestration and API surface
• Apache Spark for analytics processing
• Kafka for real-time streaming
• Redis and RabbitMQ for messaging
• PostgreSQL for operational logging
• Docker and Kubernetes on Robin Cloud
• Milvus and ChromaDB for vector storage
• Jenkins CI/CD pipelines
• AI Gateway for LLM governance
• GeoPandas, PyTorch, and OpenCV for AI analytics

Testing and Validation

• Anomaly detection accuracy checks
• Predictive forecasting reliability tests
• Geospatial analytics accuracy validation
• Simulation engine validation
• End-to-end telecom workflow testing
• Performance and scalability testing
• Operational integration validation

The Impact

• 85% reduction in inspection time
• 60% faster root cause analysis
• 35% improvement in work-order accuracy
• 3× faster new site decision-making
• $2.4M+ projected year-1 savings
• 10K+ site images validated monthly with zero manual review
• 5K+ cell sites analysed through multi-agent network intelligence
• 12 weeks concept to production deployment

Before vs After

"With Gen AI powered telecom operations, Rakuten Symphony is enabling predictive intelligence, intelligent automation, and faster network decision-making at enterprise scale."

— Prashanna Rao, Head of Engineering, GoML

Key Takeaways for Telecom Operations Teams

Common Challenges

• Disconnected telecom operational systems
• Reactive network troubleshooting workflows
• Limited predictive intelligence in day-to-day operations
• Manual project forecasting and operational analysis
• No conversational AI layer for telecom analytics
• Inefficient resource allocation and workflow orchestration

What to Prioritise

• AI-powered network optimisation from the start
• Conversational AI for real-time telecom analytics
• Predictive forecasting and anomaly detection integrated end-to-end
• Intelligent orchestration across telecom workflows
• Proactive maintenance and recommendation engines
• Scalable cloud-native AI infrastructure, not bolt-on tooling

Build the Same Platform for Your Telecom Operations

If your telecom stack is a set of capable systems that do not reason together, our Claude developers can scope a similar unified platform on Claude via Amazon Bedrock in a 12-week engagement.