Mavenir unveiled an Agentic Service Assurance Framework designed to automate complex network operations across multiple domains while allowing operators to retain existing infrastructure.

The vendor stated the TM Forum-compliant, multi-agent system combines an intent orchestrator with a layered agentic ecosystem to help detect, diagnose, recommend and resolve network faults faster.

Mavenir positioned the framework as a step toward higher operator productivity and autonomous network operations.

The vendor said network operations across 5G, cloud-native and IP domains are becoming increasingly fragmented and expensive to manage at scale. Traditional assurance systems can identify alarms but often struggle to determine root causes, while the retirement of experienced engineers risks taking years of institutional knowledge out of operations teams.

Multi-vendor environments add another layer of complexity by creating data silos which individual tools cannot easily correlate, according to Mavenir.

At the heart of the framework is Mavenir’s Intent Ops engine, which observes how network operations centre teams work, learns patterns behind successful issue resolution and converts those workflows into repeatable automation templates with explainability and guardrails.

The company explained the workflows are validated against a human baseline before running autonomously, with vetted automations published to an expanding orchestration catalogue.

The framework supports cross-domain monitoring, correlation and root-cause analysis, with closed-loop remediation built on Mavenir products.

It also connects with existing OSS AI agents through the agent-to-agent protocol defined in TM Forum’s IG1453, which Mavenir stated enables operators to preserve prior technology investments while extending automation across the network stack.

Mavenir CEO Pardeep Kohli told Mobile World Live the foundation AI agents are designed to automate 60% to 75% of routine network operations work, to help operators lower costs, improve service quality and reduce the need to train staff on repetitive tasks.

“In a way, you have a kind of personal assistant always watching you, but this personal assistant is for the network,” he said.

Mavenir did not say when it will be available but a representative stated the initial release is being trialled in customer deployments and future feature releases will be delivered through software upgrades.

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