Roaming for Autonomous Networks – Deployment
Case Studies & Use Cases
/ Roaming for Autonomous Networks – Deployment /
After Detect and Analyse, the final stage in building an Autonomous Network is safe, reliable deployment. Whilst theoretically this is the most challenging stage, it is where CORTEX has its most significant pedigree. CORTEX executes partner changes across multi-vendor devices with built-in roll–back and post-change verification, ensuring compliance and service continuity. Our Customer have been trusting CORTEX with this for 25 years.
Once partner and hub changes have been validated and their network impact assessed, Operators face the most critical step: executing updates on live home network devices. Traditionally, this process involves manual command preparation, human approvals, and engineering teams applying changes across multi-vendor infrastructure.
This manual approach is time-consuming and introduces significant risk. Errors in device commands, mis-sequenced updates, or delayed rollback can cause outages, degrade roaming services, and damage both reputation and wholesale revenue streams.
This operator was processing over 100–150 configuration updates per month across core devices (HLR, HSS, MSC, SMSC, MME, SGSN). The goals were to:
- Automate pre- and post-change configuration checks to ensure service stability.
- Generate multi-vendor device commands (SSH, Telnet, REST APIs) based on the approved target state.
- Integrate with existing approval workflows for Core Network Engineering.
- Enable safe rollback mechanisms in the event of failures.
- Maintain a full audit trail and automatically update Trouble Ticketing systems for compliance.
CORTEX was deployed to automate Stage 3 CORTEX Roaming Deploy for Automated Configuration Deployment. The system first runs pre-change validation checks to confirm that devices were in a known state, then applied pre-change maintenance by placing affected devices into controlled states.
It generates configuration commands tailored for each vendor and device type, submitted them for approval, and—once authorized—executed them automatically via SSH, APIs, or through tickets routed to engineering teams.
If failures occur, CORTEX triggers automated rollback procedures, restoring prior configurations or marking devices out of service with notifications to stakeholders. After execution, the system performs post-change validation checks and returns devices to service. Recurring stability checks are scheduled (12–36 hours) to confirm longer-term health.
Throughout, CORTEX keeps all Trouble Tickets updated with the latest execution status, ensuring complete visibility and governance.
Reduction in network execution time
Reduction in configuration errors
End-to-end audit trail coverage
The Operator significantly reduced risk and accelerated implementation by shifting from manual execution to fully automated network configuration.
The solution:
- Reduced execution time per change by 85%, from hours to minutes.
- Improved service reliability with automated validation and rollback safety nets.
- Ensured end-to-end auditability, with all actions logged and integrated into ticketing systems.
- Delivered a repeatable automation framework that could be reused across different device domains and geographies.
- Strengthened customer experience by ensuring roaming updates reached the live network with speed and accuracy.
Design to Deploy Time – 6-9 Months
Approximate Software Cost – $50,000 per year
Return on Investment – 2 months after go-live.
The Operator significantly reduced risk and accelerated implementation by shifting from manual execution to fully automated network configuration.
The solution:
- Reduced execution time per change by 85%, from hours to minutes.
- Improved service reliability with automated validation and rollback safety nets.
- Ensured end-to-end auditability, with all actions logged and integrated into ticketing systems.
- Delivered a repeatable automation framework that could be reused across different device domains and geographies.
- Strengthened customer experience by ensuring roaming updates reached the live network with speed and accuracy.
Design to Deploy Time – 6-9 Months
Approximate Software Cost – $50,000 per year
Return on Investment – 2 months after go-live.