Fragmented troubleshooting
Evidence for one incident sat in several consoles, so every investigation started by hand.
Case study
AI-powered network observability for a major telecommunications provider
A North American carrier rebuilt its network operations with MIR Digital Solutions on the PulsarOps AI event intelligence platform.
At a glance
- Sector
- Telecommunications
- Region
- North America
- Delivered by
- MIR Digital Solutions
- Platform
- PulsarOps AI
We do not name the provider. We describe deployments only as enterprise NOCs worldwide.
Context
A national network, and a triage workflow that stopped scaling with it.
Events arrive from every corner of the infrastructure, across vendors that do not agree on a log format. The provider wanted that work changed, not another console.
The challenge
Three problems. None of them was a shortage of data.
The signal was already in the logs.
A multi-vendor infrastructure
Routers, switches, firewalls and load balancers, each with its own log format.
Reactive vulnerability management
Security awareness arrived after the event, never ahead of it.
One incident, split across two consoles
Core router Aggregation A one incident timeline
- link state down
- interface flap
- bgp session reset
- mac move detected
- protocol down
- uplink error rate
Two device timelines zip into one order.
What the platform did
One platform for correlation, visibility and security awareness.
It runs alongside the monitoring the NOC already had.
01 · Intelligent insights
Automated event correlation across the infrastructure
- Correlate events across multi-vendor infrastructure.
- Surface what matters before someone goes looking.
02 · Conversational troubleshooting
Ask the network a question in plain language
- Query event logs, configurations and topology in plain language.
- Get a written summary with the evidence behind it.
- Get the recommended next step.
03 · Proactive vulnerability intelligence
Security awareness that arrives before the incident
- Network and security signals in one view instead of two.
- Vulnerability intelligence that runs ahead of the event.
The outcome
What changed for the team.
Four things the provider reports in the published study.
01
Improved operational efficiency
Same team, same infrastructure, correlation handled for them.
02
Reduced manual effort
Fewer hours assembling the picture, more spent acting on it.
03
Accelerated issue resolution
Investigations start from a grouped incident and a next step.
04
More proactive management
Early warning and vulnerability intelligence beside the events.
From the published case study, 5 August 2026. No deployment figures are claimed here. Contact sales@pulsarops.ai.
The business case
What a deployment of this shape is modeled to return.
Model figures from the CTO value brief, not from this provider.
Request the CTO value briefAn eight hour triage starts with finding the window
One day of data 13:58 – 14:06
fault window
- 00:00
- 06:00
- 12:00
- 18:00
- 24:00
A day of data, one narrow fault window.
- Incident recovery
- 50-75%
- faster incident recovery
- Return on investment
- 228%
- annualized ROI
- Payback
- 3.7 mo
- payback period
- Cost efficiency
- 2-4x
- more cost-efficient over three years
Three-year estimate: five-person NetOps team, ~125 incidents/yr, triage cut from 8 hours to 1.
How it works
One platform. Three stages.
The same pipeline sits behind every deployment.
-
01 Ingest @ scale
Data as it arrives
- Syslogs and application logs
- Configs and inventory
- Tickets and topology
Real-time and historical, multi-vendor
-
02 Analyze @ scale
Analysis and evidence
- Latest LLMs, agentic RAG
- ML classification and anomaly detection
- Pattern-based correlation
Millions of events, minutes not hours
-
03 Insights @ scale
Insights and remediation
- Early warning trends
- Root cause analysis
- Recommended next steps
Human-centric, evidence-backed
On-premise
Runs inside your perimeter. Nothing leaves your network.
Sovereign-ready
In-country deployment for government and regulated industries.
Cloud-agnostic
Your VPC on AWS, Azure, or GCP. Your keys, your controls.
Read next
More from the resource library.
MIR PulsarOps AI Origin Story
How a national telecom outage turned into a log pipeline and an AI assistant.
Where PulsarOps AI sits next to the alternatives
Log analytics, monitoring suites and cloud-only AIOps, side by side.
Briefs, guides and explainers
The platform brief, the CTO value brief, two explainers.
Book a demo
See PulsarOps AI running on your own data.
Thirty minutes with an engineer. Bring a real incident.