Australian Spatial Analytics is a data analytics company based in Brisbane, Australia. The company employs a uniquely talented workforce and was established to provide high quality data extraction and analytic services to industry and governments across Australia & the Pacific region.
Australian Spatial Analytics (ASA) is a registered not for profit enterprise. We provide life changing employment opportunities for those with autism. Importantly, we provide a fertile environment where talented individuals with exceptional skills in pattern recognition, problem solving and memory retention can absolutely flourish.
At ASA we love our work, we love our spatial data and we respect our incredibly talented locally sourced staff. Nothing makes up happier than delivering valued solutions to you – our customers.
We are proudly data hungry and open for business.
Core Australian Spatial Analytics Objectives:
- Deliver a trusted national operation that provides quality data extraction and analytic services to Industry and Government.
- Expand and build a loyal customer base through high levels of quality and innovation, in proving a top-level domestic operation
- Provide employment and life changing opportunities for those on the autism spectrum and other disadvantaged Australians.
Examples include change detection of lidar and photographic imagery for asset management and recording of ‘as-built’ infrastructure (roads, powerlines, buildings, plant and equipment).
Local spatial data services
Enable local outsourcing and/or focussed specialist data services whilst managing sovereign and supply chain risk.
Unique model – talented workforce
A very effective way to support and achieve social procurement objectives and foster inclusive workplace environments.
Enhanced customer experience
An accessible, scalable, on-demand customer experience, free from call centres, time zones, communication latencies, and international management overheads.
Examples include change detection of lidar and photographic imagery for asset management and recording of ‘as-built’ infrastructure (roads, powerlines, buildings, plant and equipment.
This relates to the manual annotation of data to assist with the creation of ‘reviewed’ library data-sets for input into AI and machine vision algorithms.