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ML solutions are often hard to achieve, due to lack of integration or perceived unreliability. Building on our strong engineering skills and experience in implementing complex solutions, we make sure these projects get to the finish line. Understanding how to deliver ML as coherent features that behave predictably is key to the success of these solutions. We help you tackle these challenges and ensure that capabilities and the value they add make it into the hands of your users.
When dealing with rich media (documents, images, sound, videos), ML lets you leverage their contents. Thanks to an automated approach, covering simple cognitive tasks and managing extremely large collections becomes feasible, enabling use cases that rely on your media.
ML can help segmenting users and predict the «next best move» to increase their lifetime value towards your business, maximize their likelihood to purchase your products and services, or even decrease their probability to churn.
ML can help adding smart components to existing software by creating more value to end users and your organization. There is usually some ML behind recommender engines, output suggestions or predictive indicators that help the user to make a better choice.
Artificial Intelligence (AI) and Machine Learning (ML) models are taking increasingly central roles in software. A great number of crucial processes relies on these capabilities and the models become an irreplaceable part of modern businesses.