From Big Data through Machine Learning to the Internet of Things, we are interested in everything when it comes to coding. Check our main fields of expertise and discover the projects we have recently taken on.

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Snapcart is a new-generation market research company headquartered in Jakarta with offices in Singapore and Manila.

The company has a consumer mobile application that lets users take photos of their receipts and upload them to Snapcart’s system. In return, they earn cashback while Snapcart uses their data for market research for clients like P&G, Unilever, J&J, and more.

We helped Snapcart automate its data-processing pipeline to minimize human interaction in the process thus making the pipeline faster and scalable.

We developed a real-time, scalable, and easily extendable Google-Cloud-based data warehouse and reporting solution for Dagrofa, one of the biggest retailers in Denmark.

Today, the company is able to collect and analyze data about its core activities (e.g. sales, marketing, and logistics), make data-driven decisions and predictions, and gain insights.

We helped the digital marketing company Carussel to move its digital solution to the cloud from its on-premises infrastructure.

By migrating the infrastructure to Google Cloud, Carussel has a solution that meets high service-level standards, utilizes less operational workload, and extends easily on new market introductions.

Furthermore, with Google’s pay-as-you-go pricing model, Carussel can transform its opex budget into features that really matter.

We helped one of the largest Central and Eastern European low-cost airlines ‒ Wizz Air ‒ to connect online Google Analytics 360 data to their data warehouse to get combined insights.

By integrating these two data sources with Google BigQuery, Wizz Air is able to gain valuable business insights.

We developed Asia’s largest brewing company a time series forecasting with state-of-the-art gradient boosting methods. It included a forecast breakdown by dimensions such as geographies and products. Thanks to this new machine learning solution, the company is now able to make precise demand prediction for brick-and-mortar and hybrid retailers as well as supply-demand optimization for marketplaces and on-demand services apps. As a result, they are currently able to forecast the next month’s results with a 96% reliability.

We helped one of the largest media companies in Hong Kong create recommendations of keywords and master tags on Google ML Engine. We incorporated collaborative filtering to find the most relevant keywords and master tags for each user. We developed the minimum viable model development in one month and provided documentation to enable knowledge transfer and operationalization by the client.

We helped one of the biggest budget airlines in SouthEast Asia enhance its processes and drive ROI with the help of machine learning. The developed solutions include prediction of purchase (buy / no-buy) for each ancillary category (such as seat, food, baggage) and recommendation of most likely items within each ancillary category (such as for seat: aisle - premium seat). We focused on production-readiness for A/B testing and ensured knowledge transfer about processes and best practices around building the machine learning pipeline.

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It would be very difficult to fit all the stuff we’d love to show you on one website. If something you’ve seen has struck a chord with you, or if you’re keen to know more, drop us a line and let’s talk!

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