Functional Data Analysis
Our data science team works in support of client functional teams to improve data management, from integrity to inspection to Turnaround planning - we cover and support a wide range of functional disciplines.
Our goal is to help our clients identify problems or challenges in their use of asset data - and then to create a cost-effective and manageable solution to overcome those problems. Solutions can range from simple data cleaning and classification all the way to complex Artificial Intelligence (AI) processes which auto-classify and label data - enabling the automation of key functions.
Accelerating the data journey
Our technology and data team works in support of our clients to expedite their data journey. Our teams leverage AI and Machine Learning (ML) coupled with the latest technologies to solve customer challenges. The fundamental premise of the teams' work is to deliver efficiency to users and help our clients better use their data - automating away mundane and repetitive tasks.
At AIS we offer a variety of flexible services that are tailored to your unique business and project requirements:
Data analysis & validation
By analysing current workflows and processes within the business, this service focuses on defining pain points and validating the underlying data to provide value. Typically completed in 4 weeks, we also perform data exploration and data mining techniques to further analyse the data.
Proof of Value
This service builds on the work done through exploration and validation to perform data mining and prototyping machine learning (ML) models where possible and appropriate. This process involves working closely with clients to define and create features that can be used in the creation of models.
Proof of Concept
The proof of concept service builds, deploys and validates models against defined performance criteria for a finite data set or use case. A cloud deployed application will also be created to demo the model/system developed.
Pilots/Minimum Viable Product
This service involves the entire process of prototyping, deployment and integration of model in a cloud platform that can then be integrated into other systems/applications.