We’ve been using Machine Learning to operate and optimize mobile and fixed networks and reduce CapEx intensity, overcoming the exponential data growths pressurizing investments and degrading performance.
Thanks to our domain experts and innovative software solutions, we are capable of efficiently troubleshooting services end-to-end accelerating performance improvements in growing complex multi-system, multi-vendor and multi-service networks.
Together with our worldwide customers and data science team, we have developed advanced analytics and improved processes that eliminate outdated manual tasks through automatic data sources correlation, automated diagnostics and closed-loop actions.
Winning national benchmarking campaigns has become a top priority for many operators. Aspire cost-efficient model and proven methodology has enabled our customers to outperform in such benchmarks thanks to our mix of deep technology expertise, +20-years’ experience and innovative solutions.
Winning a public performance benchmark and cost efficiency can go together
Public performance benchmarks are a priority for many Communication Services Providers (CSPs) around the world, and an integral part of their business strategy every year. Preparing for them can be expensive, labor intensive and inefficient due to the need for extensive active testing (e.g. drive and walk tests) and the optimization process that will require improvements. To find out how Aspire can help read our latest whitepaper.
Rise of the Network: Delivering Improved Experience Without CapEx
Aspire Technology has supported numerous network operators through end-to-end optimization to improve customer experience and maximize their return on investment.
This success story gives an overview of a 6-week project where Aspire faced a particularly challenging optimization project. Our customer was suffering from high congestion, external interference and a very high 2G-only device penetration, which had resulted in poor voice and data experience, continuous complaints and a high rate of churn.