From Legacy-IN to Agentic AI: Why Carriers Need Platform Expertise

AI agents in the telco sector need more than just good dialogue

An AI agent is not successful in the telecoms sector simply because it sounds natural or provides a linguistically correct response to a query. It is successful if it can operate reliably within a highly complex, established system landscape.

This is precisely where telco automation differs from many isolated AI applications. A telco service does not run in a self-contained front-end. It operates within an architecture in which IMS networks, signalling, media servers, messaging systems, BSS/OSS, CRM, billing, provisioning and customer data must all work together seamlessly. At the same time, there are requirements that are non-negotiable in the telco sector: The service must be multi-tenant, geo-redundant, highly available, auditable, secure, scalable, resilient to load and subject to regulatory oversight.

The key question is whether an AI agent can be integrated into operational carrier processes in a controlled, traceable and stable manner.

Why telco services need a telco-grade platform

Carriers do not operate simple, standalone applications. They operate service landscapes that have evolved over years or decades. Legacy IN, number translation services, Voice VPN, IVR, contact centres, recording, messaging, NG112 and customer care are not isolated functional modules. They are interlinked, utilise shared network resources and must be further developed whilst the system is in operation.

A modern Service Delivery Platform provides the technical foundation for this. It thus serves as a versatile basis for various components: signalling, routing, media, messaging, AI solutions, backend integration and service creation within an architecture that supports both existing networks and new cloud-native environments – for standard and customised applications.

New services do not need to be reintegrated every time. Instead, they can be built on a platform that continues to utilise existing network logic whilst simultaneously delivering new services more quickly.

From connectivity to B2B services

For telcos, the business leverage arises where platforms turn network functions into marketable services. Connectivity remains the foundation. However, growth is increasingly driven by services that telcos can offer directly to their customers.

• Number translation and Voice VPN for business customers with distributed locations

• IVR, voicebot and chatbot services for customer care

• Messaging, RCS and API-based value-added services

• Contact centre and recording services from the carrier cloud

• Omnichannel bots and AI agents

• AI-based analytics, transcription and agent assist

• NG112 and critical communications services

These services require telcos to combine their network expertise with service expertise. It is not just a matter of providing a service from a technical perspective. What is crucial is being able to operate this service as a B2B offering that is multi-tenant, scalable, manageable and billable.

This is precisely where platform expertise becomes a competitive advantage. It enables telecoms to develop their existing infrastructure cost-effectively and to generate new value in addition to simply providing network services.

Agentic AI is transforming the requirements for service platforms

Agentic AI is redefining the expectations placed on automation. Traditional bots answer questions or guide users through predefined dialogues. Agentic AI can pursue objectives, identify missing information, plan intermediate steps and orchestrate workflows.

An autonomous AI agent should do more than simply provide information. It should, for example, check customer data, change routing rules, activate service options, create tickets, generate conversation summaries or trigger backend processes. This must not happen without supervision. The AI agent requires access to data, tools and workflows. This access must be authorised, restricted, logged and verifiable. Otherwise, it poses a risk to operational security, data protection, compliance and service quality.

How can AI agents’ access to back-end systems and data be implemented in a way that ensures data sovereignty and control?

The platform as an enabler for controlled AI back-end integration

For AI agents, the CreaLog SDP provides the necessary control and integration layer between AI and the backend. It provides the architecture through which AI components can securely access data, tools and workflows without directly or uncontrollably interacting with operational systems.

Integration mechanisms such as the Model Context Protocol, or MCP for short, are key building blocks within the platform architecture. They help to separate AI-based reasoning from backend execution. The AI agent therefore does not have unrestricted freedom to access any system resources. It can only utilise defined, authorised capabilities provided by the platform via controlled interfaces. In this way, the platform architecture empowers AI agents to act without relinquishing access control. They are used to manage policies, rights, roles, logging and execution logic. MCP servers can provide authorised functions, data access and workflows; the MCP client mediates server access in a controlled and integrated manner, within the platform’s governance and operational logic.

This is how innovation and operational reliability come together: AI can understand customer concerns, conduct convincing dialogues, prepare decisions and orchestrate processes. However, actual access to backend systems does not take place directly via the LLM, but is controlled via the platform. At the same time, this architecture lays the foundation for connecting business customers’ systems and data to telco services and systems whilst maintaining data sovereignty. This enables telcos not only to automate their own processes, but also to provide secure, controlled AI-based services in a multi-tenant environment for their B2B customers.

Legacy IN remains relevant if integrated correctly

Many telcos face the challenge of integrating new AI and cloud capabilities with existing IN, TDM, NGN, IMS and BSS/OSS landscapes. These legacy environments are not simply dead weight. They contain business-critical logic, customer data, routing rules and established service processes.

A strong platform strategy does not abruptly replace these investments. It integrates and modernises them. This enables telcos to continue operating existing services, migrate them and, at the same time, roll out new AI-based services.

This is particularly important because telco transformation rarely takes place on a greenfield site. New services must be developed whilst operations continue. Platform expertise therefore also means migration expertise: services are modernised step by step without compromising stability and availability.

What really counts in the end

It is not the demo that determines the success of an AI agent, but its production operation.

What counts is whether the service runs stably.

What counts is whether customers reach their destination faster.

What counts is whether business customers receive new services.

What matters is whether existing network investments can continue to be utilised.

And what matters is whether AI is controlled, integrated and operated to telco-grade standards.

AI agents become relevant for telcos when they are not viewed as isolated applications, but as an integral part of a platform architecture. Only when network logic, business processes, backend access and AI orchestration are brought together does genuine business value emerge.

Conclusion: Platform expertise is becoming a prerequisite for secure AI in the telco market

Telco operators that currently run a robust Service Delivery Platform have a strategic foundation for the next stage of development in telecommunications. Not only can they operate existing services more efficiently, but they can also offer new B2B services, customer care automation and controlled AI agent scenarios.

Agentic AI derives its value not from maximum autonomy, but from controlled decision-making capability. This is precisely why a telco-grade platform is needed: integrated, highly available, auditable, multi-tenant and capable of interfacing with established network and backend environments.