Telecom
Every autonomous action starts with the right data.
The agentic models are ready. The data is not. Autonomous networks and operations now reroute traffic and fix faults without human intervention. The point of failure is when foundational data arrives unstructured, in part or late. That’s the gap. It’s not about intelligence. It’s the supply.
AI alone doesn’t fix bad data.
Data Mediation does.
The primary barrier to AI adoption in telecoms is not model performance it’s data quality and accessibility. Appledore Research, Analysys Mason (across 84 CSPs), and STL Partners all reach the same conclusion. Data mediation determines whether AI systems receive data that’s accurate, consistent, and fresh enough to act on.
AI models fail on dirty data
Data collection and quality, not model selection is the defining constraint on telco AI performance. Fragmented, delayed, or poorly formatted data limits an AI agent’s ability to reason accurately and act with confidence.
DigitalRoute validates, normalises, and enriches data at source before it reaches any AI system.
Agentic AI demands machine-speed data
AI agents interact with systems continuously and at machine speed, generating dynamic and unpredictable data flows. An agent acting on data seconds late, may be acting on a network state that no longer exists.
DigitalRoute delivers real-time stream processing so agents always act on current state.
Data silos block end-to-end visibility
TM Forum L4 Autonomous Networks, actively targeted by 30+ global operators requires cross-domain, closed-loop automation. That’s impossible without a single, trusted view of network state across all domains and vendors.
DigitalRoute consolidates data from any vendor, any domain, into a single source of truth for autonomous operations.
Traditional network management approaches are no longer sufficient to meet the demands of 5G and beyond. We are pioneering AI agents for networks… towards autonomous, self-healing networks.”
— Abdu Mudesir, Group CTO, Deutsche Telekom (MWC 2025)
The case for off-the-shelf mediation has never been stronger.
Modern telco data mediation is a mission-critical engineering discipline. The gap between what specialist vendors deliver and what internal teams can realistically build and maintain has widened considerably. For most CSPs, the build route is a strategic miscalculation of cost, talent, and time.
| DIMENSION | BUILD YOUR OWN | OFF THE SHELF — DigitalRoute |
|---|---|---|
| AI & 5G readiness | Architected around requirements known at point of design. Real-time streaming and AI-ready data formats require significant retrofit | Real-time stream processing, event-driven architecture, and AI-ready data delivery already in the platform — not a roadmap item |
| Revenue Leakage | Elevated risk — validation logic immature in early years. Forrester data: avg. 10% of operating income lost pre-implementation | Pre-validated exception handling refined across 100+ operator deployments. Revenue assurance built in. |
| Total cost of ownership | Consistently underestimated. Indirect OPEX — engineering headcount, security patching, tooling — accumulates fast and is rarely modelled at inception | Known and predictable. R&D investment spread across a global customer base. No key-person risk from architects who built the system |
| Regulatory & compliance | Bespoke effort — 3GPP, TM Forum Open APIs, GDPR data lineage all require specialist engineering | Standards alignment built in. Continuously updated to match 3GPP releases, TM Forum SID, and regional compliance requirements |
| Technical debt | Accumulates from day one. What fits today becomes a constraint in five years while vendor platforms improve through continuous R&D | Continuous product investment. Decoupled from your network infrastructure — upgrade without breaking the stack |
BILLING & REVENUE
Where it started.
Still business-critical.
Telco created its own data complexity challenges. Every call record, data session, roaming event, and partner transaction has to be captured without error and delivered to billing, fraud, and revenue assurance systems in time to matter. That’s still true and the stakes are higher than ever.
- Multi-vendor CDR collection and real-time normalisation
- Online and offline charging with 5G monetisation support
- Partner settlement, interconnect billing, and roaming reconciliation
- Revenue assurance and fraud detection clean data in, no leakage out
- Usage-based and consumption billing for B2B and enterprise services
NETWORK INTELLIGENCE
Same source data.
Untapped opportunities.
Revenue Management defines what an event is worth. Intelligence Management reports what’s happened, all from the same data. The same session records, the same signaling, the same trace files. A dropped call is both a billing event and a service failure. Most operators built two estates to manage them. One foundational data layer answers both questions.
- Subscriber-level trace across RAN and core, without a probe estate to maintain
- Fault and performance data normalized across every vendor, before it reaches your assurance tools
- NWDAF data collection and delivery
- Network, billing and interaction data unified into one live view of customer experience
“The advantages of using DigitalRoute continue to be significant. Today, we have fewer systems and databases to maintain. The architecture has been simplified and we continue to become more efficient.”
— Manager, Mediation Application Development, Vodacom
Kubernetes-native mediation. On your infrastructure, on your terms.
For regulated European operators, “move to the cloud” usually suggests a private cloud, which normally translates into a Kubernetes-based deployment. Containerized, microservices-based, and fully under their control. The alternative has been staying on monolithic legacy on-premise stacks. DigitalRoute ends that trade-off.
Data mediation has been evolving for 25 years. So have we.
Telco invented large-scale data mediation. DigitalRoute has been at the forefront of its evolution from call data records to convergent charging to real-time AI data operations.
FAQ
Common questions
Data mediation is the operational layer that collects, validates, normalises, enriches, and routes network and service event data to the downstream systems that depend on it including billing, revenue assurance fraud management. It sits between the network infrastructure and every system that consumes usage data.
AI systems and agentic network automation are only as capable as the data they receive. Mediation determines whether data arrives accurately, consistently, and in time to act on. Appledore Research, Analysys Mason (surveying 84 CSPs globally), and STL Partners all identify data quality and accessibility not AI model performance as the primary barrier to AI adoption in telecoms.
Traditional mediation platforms were designed primarily for batch billing and CDR processing. Next-generation platforms are cloud-native, Kubernetes-based, capable of real-time stream processing, and support complex multi-vendor and multi-domain data integration for AI and automation use cases alongside traditional billing.
TM Forum’s Level 4 Autonomous Network defines cross-domain, closed-loop automation in which networks can autonomously assess real-time conditions and adjust operations based on high-level intent. More than 30 global operators are actively working toward this target. Achieving it requires mediation infrastructure capable of delivering trusted, real-time, high-quality data without delay or gap.
Independent analysis consistently favours buying from a specialist vendor. Building a production-grade mediation platform typically takes 18–36 months versus 3–9 months with an established platform. Forrester Consulting research found operators leaked an average of 10% of operating income before implementing specialist mediation. Mediation is not a source of competitive differentiation. Operators win on network quality, service speed, and customer experience all of which depend on a mediation layer that works.