The Right Stuff
Software can do almost anything, but the market’s needs are specific. Finding the essential aspects of these requirements is an exercise in analysis and imagination, and it’s what we do best.
From the business case to the code and back our products make sense. Pain points are addressed head on with appropriate, cost effective yet powerful technologies, replacing impossible problems with an obvious course of action.
Power on Tap
Unused compute capacity is a silent subsidy to hardware manufacturers that prevents otherwise viable software products from seeing the light of day.
As advances in hardware speed have tailed off not all developers have picked up the performance baton — but the Rocketeers have. Hardware running our products is worked to its silicon bones.
We also think you shouldn’t have to pay for hardware that you don’t use. We are experts in on-demand serverless cloud technology, paying by the second for the compute we use.
Secure, Flexible Points of Presence
Trusted points of presence allow our products to do their work where it makes the most sense — handling sensor data near its source to protect privacy and network bandwidth, or driving physical hardware to alert or assist staff.
Our fleet of camera and sensor connected devices is installed across the branch networks of leading financial and retail organisations. The secure provisioning, remote deployment and monitoring infrastructure we’ve built allows rapid deployment of new features and a clear audit trail to show exactly what software is running on any device at any time.
Got a Haystack? Find Those Needles
Everything can be optimised if you have an army of untiring, affordable servants to observe the as–is and weigh billions of alternative to–bes.
Recent leaps in machine learning are just the latest in a series of techniques developed over the last century. All of them are required to solve problems at business–level time scales and scopes.
Companies narrowly focussed on the newest and shiniest technologies struggle to apply machine learning without a focus on the business domain and the techniques required to connect it to machine learning inputs and outputs. Rocketeers love the shiny stuff, but seeing it put to work is even better.