Cloud-native 5G and mobile core software for telecom operators
Mavenir builds AI-first network software for mobile operators, with deployments across 300+ carriers in 120+ countries. The tech stack reveals a modernization-in-progress: heavy Oracle EBS + EPM for enterprise operations, paired with Kubernetes, gRPC, and cloud platforms (AWS, GCP, Azure) for product delivery, plus emerging AI tooling (PyTorch, TensorFlow, LangGraph, Langchain). Active projects span agentic AI integration and cloud-native network core development, while pain points center on legacy ERP maintenance and authentication migration—suggesting a multi-year shift from monolithic telco software toward containerized, AI-driven architectures.
Notable leadership hires: Shift Lead
Mavenir develops cloud-native software for 5G and mobile networks, serving mobile operators globally. The product line spans Radio Access Networks (RAN), mobile core, packet compute, IMS, and business messaging, with a stated focus on AI-by-design solutions. The company operates across the full operator stack—from radio access through service delivery—and maintains significant internal complexity: Oracle EBS underpins financial and ERP operations, while a modern product stack runs on Kubernetes and cloud platforms. Current hiring is engineering-heavy (14 of 25 active roles), concentrated in the United States and India, with a notable concentration of senior-level positions.
Mavenir uses Oracle (EBS, EPM, SQL, Reports), Kubernetes, Docker, C++, Go, and cloud platforms (AWS, GCP, Azure). For AI, the stack includes PyTorch, TensorFlow, LangGraph, and Langchain. Databases: MySQL, PostgreSQL, MongoDB. gRPC for service communication.
Active projects include agentic AI integration, cloud-native network core development, AI and network strategy development, process automation via Power Platform, IMS SBC solutions, and customer POC activities.
Mavenir's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.