Overview
One of the UAE’s leading telecom service providers partnered with Al Rostamani Communications to enhance the efficiency of its communication infrastructure and maintenance operations nationwide. For a telecom provider, fast and reliable maintenance is critical to ensure uninterrupted service and customer satisfaction. Al Rostamani Communications designed and deployed AI-powered tools using computer vision technology, enabling the customer to streamline operations, reduce manual dependencies, and improve service delivery in a sector increasingly driven by digital transformation.

Challenges

• Heterogeneous systems: The customer’s Intermediate Distribution Frame (IDF) network lacked standardisation in both equipment and technician expertise, increasing management complexity, integration difficulty, and operational costs.

• Stringent compliance and zero downtime: As a telecom operator, there was no tolerance for downtime during maintenance. All implementation activities had to be completed flawlessly without disrupting live services.

• Sub-contracting challenges: Field maintenance was performed by third-party vendors, relying on manual reporting. Only 3 percent of jobs were reviewed and approved on the same day, 60 percent within a week, and 37 percent within a month, delaying visibility and corrective actions.

The Solution
Al Rostamani Communications designed an AI-driven field-operations quality assurance system that leveraged computer vision to automate monitoring and validation processes across maintenance tasks. The system featured:

1. Automated quality assessment: Quality checks executed on images captured by field technicians, enabling instant approvals at job completion.

2. Automated issue detection: Identification of common issues such as improper cabling, inaccurate labelling, or substandard patching.

3. Automated passive element detection: QA performed using unit-type indicators such as outdoor or below-grade FDHs for accuracy and consistency.

4. Image comparison: Before-and-after image validation by the operations team to confirm job quality.

5. Issues log: Automated penalty issuance supported by photographic evidence, reducing the need for manual supervision and physical inspections.

Impact

• 97 percent operational efficiency in maintenance job completion

• 42 percent reduction in defects due to real-time issue detection

• Significant time and resource savings through automation

• Improved accuracy and transparency in field reporting and documentation

Results
With the AI platform developed by Al Rostamani Communications, the telecom provider achieved a 97 percent efficiency rate in ticket closures and a 42 percent decrease in reported defects. Near real-time issue detection and digital validation streamlined maintenance workflows, while documentation accuracy improved significantly.

The customer now benefits from a data-driven, scalable, and future-ready maintenance model that enhances service reliability and operational excellence across its nationwide network.