NashTech

AI and machine learning

We work with your company to develop the infrastructure, data culture, and technological environments to fully utilise your data assets. Doing so can open up new markets for goods and services and enable improved real-time decision-making.

With the help of our expertise in data strategy and insights, artificial intelligence, and machine learning, as well as our more than 20 years of outstanding software engineering, we collaborate with you to amplify opportunities for innovation and spot risks.

Decision science

We are passing up scalable learning by emphasising a machine-centric strategy. In the era of digital platforms, we have never been closer to our clients. Many businesses have thousands or millions of contacts with customers daily, but frequently these interactions are not designed to help customers learn new things. If done wisely, we can simultaneously learn about our customers and optimise for any company metric. These are not mutually exclusive; rather, we have tools at our disposal that enable us to learn new things while also improving our companies. We are losing out on those opportunities because of misunderstandings about artificial intelligence.

Our goal here is to present enhanced strategies that enable organisations to comprehend novel methods for the effective use of AI, particularly in the area of decision science in identifying valuable cause-and-effect relationships.

Case study
Machine learning aids detection of anomalies in cancer diagnosis process

Data science and modeling

NashTech’s data sciences solution uses data modeling and statistical methods to address particular business issues. To simplify information sharing, interpretation, and decision-making, we combine the same with the reporting and visualisation framework. Self-service is another element that allows for more end-user control. Our data sciences solution covers the entire data lifecycle, including data preparation, data enrichment, exploratory analysis, model building, and model validation, as well as integration with business processes, reporting, and visualisation.

Case study
The build of a platform to find and analyse content across traditional data silos to derive new value-driven insights

AI platform foundations

Our goal here is to present enhanced strategies that enable organisations to comprehend novel methods for the effective use of AI, particularly in the area of decision science in identifying valuable cause-and-effect relationships.

Case study
Machine learning aids detection of anomalies in cancer diagnosis process

Intelligent products

We specialise in optimising everything from product creation to operations to pricing and strategy. AI and machine learning may enhance a company’s strategy while enhancing the excellent work already being done there.

All the way from opportunity identification to actualisation. The best minds in strategy, design, behavioural science, machine learning, data science, and engineering are among those we hire. We think a cross-functional strategy is necessary to overcome the most difficult problems.

Case study
The build of a platform to find and analyse content across traditional data silos to derive new value-driven insights

MLOps

NashTech makes it easier and faster to get started with ML/AI projects and seamlessly scale them to production deployments. Taking a modern machine learning application from research and ad-hoc code to a robust and scalable platform remains a key challenge for experienced data science and engineering teams.

NashTech simplifies this process with a complete suite of tools to manage, deploy, and monitor your machine learning applications, with expertise garnered over 23 years of developing ML-enabled products. With enterprise-grade security and instant deployment to cloud-native services, taking your machine-learning application from prototype to production has always been challenging.

Case study
Machine learning aids detection of anomalies in cancer diagnosis process

Redefining the way we live and work

We help your business to leverage your data assets, creating the infrastructure, data culture, and technology ecosystems. This allows us to unlock new sources of value, new products and better decision making in real-time.

We make IT simple, faster and less expensive.

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