Network AI & Care Automation for a National Telecom
Illustrative reference architecture. This is a composite engagement template built to show how Mopshy structures enterprise work. It is not a real Mopshy client, and every figure, KPI, and quotation on this page is illustrative rather than measured client data.
AI-driven network anomaly detection, self-healing runbooks, and a customer-care copilot deployed across consumer and enterprise segments.
−52%
Repeat trouble tickets
−38%
MTTR on major incidents
+18 pts
Care NPS
The bottleneck
Network incidents surfaced through customer calls before NOC noticed. Repeat trouble tickets were 41% of care volume. Enterprise customers demanded SLAs the operating model could not defend.
The system
- Anomaly detection across RAN + core telemetry with automated correlation
- Self-healing runbooks executed by NOC copilot with approval gates
- Care copilot surfacing likely resolutions during the first call
- Enterprise service dashboards with predictive SLA burn alerts
Outcomes measured, not promised
18M
Subscribers served
94%
Anomaly-to-alert precision
0
SLA breach on new enterprise tier
$86M
Annualized value
What it cost, what it returned
Investment
$9.2M program (year one)
Payback
10 months
Annualized value
$86M care + reliability value
How it is built
- Streaming telemetry from RAN + core into a network data platform
- Correlation engine grouping alarms into incidents with root-cause hypotheses
- NOC copilot executing runbooks with approval gates
- Care copilot integrated with CRM and billing
Representative engagement. This case study describes a composite of Mopshy AI's enterprise engagement patterns, delivery methodology, and observed outcome ranges. Company names, individual quotes, and specific figures are illustrative and used to communicate the enterprise pattern rather than to describe a single identified client.
30-minute working session
Find the highest-ROI automation in your business
Bring one workflow that is slow, repetitive, or leaking opportunities. We will map the bottleneck, the systems involved, and whether automation is actually worth implementing.
No obligation. If automation is not the right answer, we will say so.