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Who we are
We believe that every organisation has an ethical obligation to do everything it can to fight financial crime. We also believe the foundation to doing this effectively, and achieving strategic business objectives, is to better understand your customers, their relationships and their behaviours.
We founded Quantexa® in 2016, but it was much longer in the making. Having worked collectively for over 200 years to help organisations of all shapes and sizes get the most out of their data and systems, we had grown tired. Tired of organisations trying to solve problems using Data Lakes, AI, Machine Learning, Advanced Analytics and Big Data, but taking their eyes off the prize because they didn’t have the technology to effectively achieve real business outcomes.
To fix this problem, our objective became threefold:
1. We needed to change the convention and develop technology that is always in-line with genuine business needs.
2. We had to make ourselves capable of working in tandem with an existing ecosystem.
3. Our philosophy had to be to enable our customers and partners with our technology so they can be self-sufficient.
To achieve these objectives and create technology that is sustainable, scalable and able to evolve with the market and its needs, it is pivotally important that the technology is built upon the most current and leading technology stack. Because of this, we developed our technology using the best Open Source software available and will always do so. Understanding the demands of businesses needs we also know that for any technology to drive real business outcomes using billions of records of data, the platform has to work in both real-time and in batch.
Entity Resolution and Network Analytics
Because of these factors, and our passion for rethinking the problem, we developed revolutionary Entity Resolution and Network Analytics technology that meets all these criteria. By using this technology our customers are now able to truly understand their customers, their relationship and their behaviours, so that they can achieve genuine business outcomes, far superior to those achieved using traditional AI and machine learning