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Project context

Telecom Support Triage & Tier-1 Resolution

AI support flow for a telecom operation that classifies incoming tickets, resolves repeatable Tier-1 issues, and hands complex cases to the right human queue with usable context.

Validated conceptTelecom support operation2025

Client identity kept confidential

38%
Tier-1 resolution
Issues resolved autonomously during validation
Measured
91%
Intent accuracy
Correct classification across tested categories
Measured
87%
Handover quality
Escalations rated complete by internal reviewers
Measured

The challenge

The solution

Technology stack

LangGraphAzure OpenAICRM IntegrationSentiment AnalysisPython

The result

The validation showed that a meaningful share of repetitive support volume can be taken out of the frontline queue without breaking the customer experience. The agent resolved 38% of tested Tier-1 issues autonomously, classified intent with 91% accuracy, and produced structured escalation summaries that reviewers rated useful in 87% of handovers.

Commercially, that means human agents spend less time on repetitive traffic and more time on the cases where technical judgment actually matters. It gives the operation a realistic path to phased rollout instead of another support demo that dies after review.

Next step

Want to explore where this could land first in your operation?

Start with one concrete workflow. We assess the first agent, platform fit, and the most sensible route to production.

Telecom Support Triage & Tier-1 Resolution Case Study | Laava