Machine Learning
Astraeus’s Machine Learning service allows us to identify efficiency opportunities within public sector organisations through the effective management of voluminous and disparate data. We provide tailored solutions which transform data consistency and quality, whilst reducing cost, streamlining effort, and exploiting continuous improvement.
Engagement types
Astraeus offers organisations two principal types of engagement for machine learning services:
1. Through a discovery process, we meticulously review labour-intensive processes that are susceptible to fluctuations in quality, rely on costly resources, or are constrained by time. Discovery findings are shared with organisations to inform their understanding of how the implementation of machine learning might drive increased efficiency.
2. Alternatively, for those organisations that have already identified potential efficiency opportunities, Astraeus can instead create a bespoke proposal(s) to address the problem statement in question.
Tailored approach
Astraeus’s Machine Learning service is always tailored to each organisation’s requirements, but typically includes the following components:
A Proof-of-Concept phase to demonstrate the viability of the work in scope.
Phases of delivery that add in scope and functionality at different project stages.
Compliance workstream to ensure validation against all standards and legislative requirements to guarantee that change outcomes meet or exceed those requirements.
Audit workstream to build in checks at regular intervals to allow organisations to review the quality of the output against manually delivered results.
Training collateral and delivery for any impacted users/ process changes.
Reporting/monitoring to deliver key sets of information for ongoing use of the system and benefits realisation.
Acceptance-into-Service which is a customised process to meet the individual requirements of the project.
Benefits realisation (measured in phased delivery and following full implementation) to provide metrics on ROI and any other agreed benefits.
Machine Learning taxonomies
Machine Learning is logically split into two taxonomies:
Unsupervised learning where patterns are inferred directly from the data set, and there is no reliance on real world examples.
Supervised learning where operations teams provide real world examples and feedback to support understanding.
Where operational support is required to enable delivery, Astraeus works with organisations to establish the environment which is best suited to deliver the project and provide the relevant training and support required to facilitate successful delivery.
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