Data Science – Machine Learning & Artificial Intelligence
Driving Business Efficiencies using Artificial Intelligence, Machine Learning and Data Science methodologies across a diverse range of industries and verticals.
Find out how we saved our well known insurance client an estimated millions of dollars with our custom built system.
- Insurance fraud is at unprecedented levels costing organisations millions of dollars.
- We used in depth research and lateral thinking to save our clients an estimated millions of dollars in revenue
- We needed to create a novel bespoke system in a short timespan
We incorporated cutting edge technology by utilising the Azure technology stack to the required business processes, building up the team’s knowledge and skillsets in the process.
- Our client is charged with ensuring Melbourne’s roads and footpaths are maintained and free of faults.
- RUBIX. was tasked with building a solution to standardise and automate the existing process they utilise for detecting faults in the footpaths around Melbourne, which was manual, time consuming and subject to human error.
- On time and on budget, the Client received a solution to recognise footpath damage using an innovative image recognition technology and tailor the remediation work for the footpath damage accordingly.
We have deep knowledge and expertise from being recognised as a trusted partner and preferred supplier of Data &
Analytics for two of Australia’s Big 4 Banks.
- At the request of the Fair Work Ombudsman, our client was tasked with reviewing the previous ten years and demonstrating that they had met their Enterprise Agreement
- RUBIX. was tasked with the regular ingestion of large, complex data sets such as the employee timesheet, and employee payslip tables. The largest of these tables was updated each month and consisted of over 150 million rows
- Recognising the complex and dynamic requirements of the environment which we were working in, the RUBIX. team created several reusable resources which were utilised by both RUBIX and the BAU client team.
Our deep expertise in machine learning models allows us to identify the right opportunities, and design and develop tailored solutions for our clients
- Our client, a large insurance comparison website, wanted to provide a market leading personalised experience to potential and existing customers
- RUBIX. was engaged to develop a machine learning model to classify customers into segments and predict which customers would respond best to certain promotions, offers and channels of communication
- On time and on budget, the Client received a machine learning solution and a suite of analytics tools that are
continuously evolving and learning about their customer behaviours, and updating their recommendations
Our client reported a 12% decrease in employee turnover rate for the next financial year as a direct result of the RUBIX model’s outputs, along with growth in employee satisfaction surveys with a sentiment score increased by 22% in positive sentiment.
- Even for large companies, success or failure can depend on a small number of very highly skilled employees.
- RUBIX were engaged to develop a ML solution that was able to ingest and understand employee feedback and identify those that were at risk of attrition
- Using our previous experience in Data Science and productising machine learning models into an existing environment with legacy systems, RUBIX were able to successfully deploy the model into the client’s existing architectural landscape with minimal compatibility issues
- The HR analytics team has become a valued advisor for the company’s executives, helping them understand how management style affects staff satisfaction, and how best to incentivise and retain key employees.
Within one month of deploying the technology, the client achieved a 50 percent reduction in resources required to audit expense reports.
- A leading global provider of comprehensive photovoltaic solar energy solutions, is an example of an organisation that is benefiting from automated real-time auditing of expense reports
- RUBIX. was engaged to develop a Deep Learning Neural Network model that ‘read’, analysed and decided on whether to approve, reject, or escalate an expense report
- On time and on budget, the Client received a machine learning model that was able to significantly reduce processing and approval times, with high levels of accuracy, allowing the client to save time and money on the process, with only complex or flagged reports escalated to a human agent.
Our solution increased the uptake of offers from the client’s app for the three test sites by 22%, resulting in increased patronage and customer loyalty.
- Number plate recognition can be used as a powerful marketing tool. Our client wanted to increase their drive through rate and app application uptake by customers
- RUBIX. was engaged to develop a solution that was able to identify and extract information from a registration plate via video in real time, correctly identify the customer and deliver promotions to the customer’s app
- On time and on budget, the client was able to deploy the final model to into their production environment at selected restaurant locations
The RUBIX approach attributed to an increase of 11% annualised loyalty seen with the patronage by returning customers.
- The goal of the client was to provide a customised in-store experience for their customers to increase their sales revenue and customer satisfaction.
- RUBIX. was engaged to provide a framework for the rapid development and deployment of machine learning models into a production pipeline. The models were then tested and ranked against each other to find the best performing combination of algorithms.
- Working closely with the client’s in-house analytics team to ensure the solution met their requirements at all stages of the development cycle, the final model was deployed to production in store, enabling the client to offer personalised offers and experiences to successfully identified clients.
Esports refers to professional video game competitions that are streamed to thousands, if not millions, of viewers online. The data collected from these competitions includes instances such as the participants, viewership numbers, results and player-specific statistics.
- Like with traditional sports, data analysts can collect data from Esports from matches to help players improve their performance and to allow the viewers to know more about how teams are performing, encouraging game involvement and a potentially creating a large audience for brand and marketing opportunities.
- Successfully extracting, managing and visualising large amounts of player data, unlocks the potential for analytics driven team coaching.
Data Science – Machine Learning & Artificial Intelligence
SEE HOW WE DO data differently
At RUBIX, we have teams of data scientists working with vast volumes of data and using machine learning and artificial intelligence practises to find patterns, derive meaningful information, and make better, faster, smarter business decisions. We’ve made our clients lives much easier using complex machine learning algorithms to build predictive models.