Digis-Capacity • smart capacity management
We enable communications services providers and mobile network operators to achieve more with their network resources, using AI and ML in their capacity management. Absorb new traffic demands, and optimise the expansions you need by using Digis Squared’s vendor-agnostic, off-the-shelf, modular Digis-Capacity solution.
Use our expertise to dynamically assist your teams
Our independent team work extensively with multi-technology and multi-vendor implementations. Our expertise and experience ensures you benefit from intelligent, vendor-agnostic capacity modelling for all network technologies (2G/3G/4G/5G).
Autonomous capacity management
- Vendor agnostic capacity modelling for all network technologies (2G/3G/4G/5G)
- Machine learning algorithms on network data, enriched with multiple data feeds from radio access network, Customer Experience Management (CEM), geolocation systems and crowdsourced data
- Predictive traffic growth based on AI-power algorithms followed by degradation preventive actions and expansions prediction
- Action-centric BM reports including KPIs, KQIs and Customers QOEs
- ROI calculations for network investments.
Our teams can use these capabilities to deliver value to service providers and mobile network operators,
- Start the smart CAPEX journey, and identify pathways to OPEX saving
- Maximize network investment ROI and help operators make well-informed, data-centred investment decisions
- Speed-up network capacity plans through our automated-predictive solution.
We can assist you right now with our ready-to-go, adaptive-modular capacity management modules, developed in-house to,
- Balance the traffic between cells & technologies
- Recommend soft actions needed
- Activate and reshuffle sites licenses
- Capacity enhancement feature recommendations
- Identify physical changes, network expansions and reshuffling required.
All our modules can be adapted in-house, to meet your exact and bespoke needs, as required.
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Digis Squared, independent telecoms expertise.