Spatialedge helps organizations improve how decisions are made using data, optimization, and AI.
See what we’ve done for our clients.
Transforming Data Warehousing with Google Cloud Platform
Spatialedge designed and implemented a data warehousing solution for a client in the retail sector, leveraging various Google tools. The solution ingested multiple on-premises data sources into BigQuery.
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Credit Decision-Making: Finding Customers and Managing Risk
To improve their value proposition for customers, our client needed models that were readily available, could score in real time, generate better credit scores, and score for various points in the credit life cycle, from pre-scoring a prospective customer.
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Implementing a Champion-Challenger Machine Learning System in the Financial Services Sector
Our team developed a machine learning framework for a major player in the South African financial services industry. We introduced a Champion-Challenger system to allow newer models to be tested against the "champion" models in a live environment.
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Streamlining Cloud Migrations for Enhanced Predictive Modeling in Banking
In the ever-evolving financial sector, leveraging data for advanced analytics and predictive modeling is crucial for staying competitive. One prominent bank faced the challenge of optimizing their data and analytics workloads
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Fingerprinting devices to identify fraud
The client faced issues with loan-related fraud on credit card machines. Vendors and sales agents were exploiting the system: vendors by fraudulently obtaining loans on multiple devices, and sales agents by earning installation commissions.
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Predictive Maintenance on Tire Failure
Spatialedge designed and implemented a predictive maintenance solution for a client in the mining industry. The solution used existing fleet data to determine when tires are likely to need replacing
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Predicting and Preventing Roadside Tragedies
In order to reduce road incidents, a government department focusing on traffic management and road safety sought to innovate their approach. They recognized the need for predictive models to forecast hotspots and enable prevention strategies.
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Assisting Retail Planners and Buyers Through a Basket Analysis Decision App
Basket Analysis involves analyzing the purchasing patterns of consumers by observing the different combinations of goods shoppers buy together. This action allows retailers to quantify consumer behavior.
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Markdown Optimization
The fashion landscape is constantly changing as new trends arise. Retailers closely monitor these changing trends to aid in purchase decisions and predict sales. As one trend replaces the other, retailers mark down stock to drive the last sales.
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