Think of a telecom network as a city’s road system. Today, every new business idea (self-driving cars, smart factories, telemedicine) needs new “lanes” and “traffic rules.” AI-enabled network transformation is like upgrading the city with smart, self-managing roads that automatically open new lanes, reroute traffic, and prioritize ambulances over commuters. This lets telecom operators quickly create and sell new digital services without rebuilding the whole road system each time.
Traditional telecom networks are rigid, slow to change, and expensive to operate, which limits the ability of operators and enterprises to roll out new digital services (5G, IoT, edge computing, industry-specific connectivity) at scale and profitably. AI-driven, software-defined networks aim to make the network more programmable, automated, and intelligent so it can support the next wave of industry innovation (e.g., smart manufacturing, connected vehicles, remote healthcare).
Deep integration of AI/analytics with telco-grade network infrastructure, plus domain knowledge about telecom operations and industry-specific use cases (e.g., manufacturing, transportation) creates a services and expertise moat that is hard for generic IT or cloud vendors to replicate.
Hybrid
Vector Search
High (Custom Models/Infra)
Inference latency and data locality at the network edge; orchestrating AI workloads across distributed edge, core, and cloud infrastructure while meeting telecom SLAs.
Early Majority
Positioned as a telecom network transformation offering that combines AI, automation, and industry consulting to enable sector-specific 5G and edge solutions, rather than just providing generic connectivity or standalone AI models.