Telecom
In a sector where telecom networks are becoming increasingly complex, the question is simple: how can quality of service be guaranteed while reducing operating costs? With the explosion of data generated by IoT and 5G, rising competitive pressure, and ever-higher customer expectations, network management and maintenance demand a new approach. Atoptima’s decision-driven AI solutions enable proactive, agile, and cost-effective planning, sizing, and operation of telecom infrastructures.
-30%
Operational Costs
Simulation
of Scenarios
÷5
Planning Time
Challenges and Issues
- Margin pressure: high operating expenses combined with intensified competition
- Quality of service and SLAs: need to maintain high performance levels while meeting customer priorities and contractual deadlines
- Data explosion with IoT and 5G: billions of new connected devices driving increasing network traffic complexity
- Responsiveness to emergencies: efficient handling of unforeseen interventions and field incidents
- Complex planning: constant trade-offs between costs, quality of service, and availability of human and technical resources
Use Cases Covered
- Network coverage survey routing: generation of schedules that account for regulatory constraints, required skills, and individual preferences
- Aerial network design: dynamic adjustment to absences, emergencies, or activity peaks through flexible optimization models
- Traffic dispatch optimization: simulation and calculation of the optimal number of staff required based on forecasted loads and growth scenarios
- Proactive intervention planning: smart allocation of resources across sites, departments, or projects to maximize operational efficiency
- Predictive maintenance: optimal assignment of agents to time slots and channels (phone, chat, email)
Benefits
- Increased operational efficiency: automation of complex planning and dispatching processes
- Reduced operating costs: lower intervention-related expenses and improved resource utilization
- Improved quality of service: greater continuity and reliability to meet SLAs and customer expectations
- Agility and resilience: dynamic solutions able to adapt to disruptions and workload peaks
- Robustness against contingencies: service continuity even in case of breakdowns, emergencies, or high demand
