High customer demand in busy areas was causing congestion and stifling data throughput, causing signal outages and delays for this mobile telecoms company. Installing additional infrastructure to expand the network capacity would be expensive, so the challenge was to predict areas of high demand and find optimal locations for new small cells.
We layered Ordnance Survey data, building outlines, clutter data, retail environment and network traffic to predict and visualise customer demand. With these foundations we developed an optimisation engine which minimised planned infrastructure costs by finding optimal locations for new small cells, taking existing network equipment and building statistics into account.
equipment saving potential tested against other tools
network service maximised
minutes per scenario plan
55% more reliable bug identification
We identified errors in C and C++ programs faster and more accurately than the existing technology.Learn more
1000X faster cable network planning
We created a way to plan fibre round a town in seconds – more than a thousand times faster than the existing approach.Learn more
20% more efficient staff schedules
We reengineered staff rotas for a global entertainment group based on predicted footfall and employee preferences.Learn more
Thank you for contacting us, we will come back to you as soon as possible