Cloud AI Modernisation for Telecoms

Modernise telecom AI workloads into production cloud platforms. Multi-cloud infrastructure for network optimization, customer intelligence, and service operations with carrier-grade reliability.

Telecommunications Challenges

Network complexity and scale

Real-time optimization requirements

Customer churn in competitive markets

Legacy BSS/OSS integration

5G and edge deployment

How Cloud AI Modernisation Solves Telecommunications Challenges

Refactoring AWS, Azure, GCP, and Oracle workloads into production-grade AI stacks. Multi-cloud RAG pipelines, observability, guardrails, and MLOps that slot into existing engineering rhythms.

Multi-Cloud RAG Pipelines

Production-ready retrieval augmented generation across AWS, Azure, GCP, and Oracle with unified governance.

MLOps Integration

CI/CD pipelines, model versioning, A/B testing, and automated deployment workflows integrated with existing DevOps.

Observability Stack

Real-time monitoring, alerting, cost tracking, and performance dashboards for AI workloads.

Production Guardrails

Content filtering, toxicity detection, PII redaction, and rate limiting to keep AI safe in production.

Use Cases

  • Cloud-native network optimization pipelines
  • Production churn prediction model deployment
  • Multi-cloud customer intelligence platforms
  • MLOps for fraud detection model management
  • Real-time service quality monitoring AI

Key Benefits

Carrier-grade reliability for AI workloads

Faster deployment of network optimization models

Unified AI governance across BSS and OSS

Cost-optimized inference for real-time operations

Multi-cloud flexibility for telecom infrastructure

Technology Stack

Kubernetes / KServeVertex AI & GKEDatabricks MosaicMLMLflow & Feature StoresSnowflake CortexAzure OpenAIAWS BedrockOracle Cloud Infrastructure AI

Ready to Deploy Cloud AI Modernisation for Telecommunications?

Let's discuss how our cloud ai modernisation capabilities can address your telecommunications challenges.

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