asseg.ai wants to solve the problems that impact enterprises and citizens around the world with a view to improving business efficiency and the quality of life for human beings.

How Can we Help you

The advances in machine learning over the last five years; the capability to store very large amounts of data cost effectively and the advances in processing power enabled through cloud computing has resulted in AI now being able to deliver on the promises of true augmented intelligence.

Using a multitude of algorithms, machine learning capability and access to hundreds of cases where AI has been effectively used, asseg.ai delivers propositions to customers to enable sense making from massive amounts of data.

By working with the foremost experts on AI, we are able to bring together capabilities, algorithms, expertise and unique insights to solve large scale problems that face enterprises and governments today and the future.

Target Sectors




Retail

Education

Financial




Mining

Agriculture

Healthcare




Security

Logistics

Our Solutions

Transforming Healthcare

Digitalization makes care affordable and available, ensuring sustainability and growing our understanding of disease.

We aim to Shift Focus from Treatment to Prevention

Importance of Transformation

AI in healthcare and medicine could organize patient routes or treatment plans better, and also provide physicians with literally all the information they need to make a good decision.

healthcare Solutions

Mining medical records:

Our healthcare solution is used to mine the data of medical records in order to provide better and faster health services.

Designing treatment plans:

Our global AI toolkit has an advanced ability to analyse the meaning and context of structured and unstructured data in clinical notes and reports that may be critical to selecting a treatment pathway. Then by combining attributes from the patient’s file with clinical expertise, external research, and data, we can identify potential treatment plans for a patient.

Health assistance and medication management:

The virtual nurse, its exclusive goal is to help people with monitoring their condition and treatment.

The interface uses machine learning to support patients with chronic conditions in-between doctor’s visits. It provides proven, customized monitoring and follow-up care, with a strong focus on chronic diseases.

Precision medicine:

• Artificial intelligence has a huge impact on genetics and genomics as well. Deep Genomics aims at identifying patterns in huge data sets of genetic information and medical records, looking for mutations and linkages to disease. A new generation of computational technologies that can tell doctors what will happen within a cell when DNA is altered by genetic variation, whether natural or therapeutic.

Farmers in many parts of the world are largely dependent on timely rainfall for harvest and subsequent profits.

Gradual onset of global warming and climate changes, over the last century, have slowly-yet steadily put this wisdom out of use.

Automating on Farming Activities

Identifying pest and disease outbreaks before they occur and calculating probability of outbreaks based on historical data, climate data, etc. and then helping farmers manage that risk in an economic sense

Monitoring crop conditions like water stress, nutrient condition, plant population, soil moisture content

Robotics in Agriculture

Agriculture robots are expected to replace human labor and can thus help overcome the scarcity of physical labor. These robots bring with them advantages such as constant work rates under a diverse array of harsh environmental conditions, a reduction in the use of chemicals and pesticides applied to crops, and the heavily sought-after concept of precision agriculture.

On the research and development side robotic agriculture introduces Image recognition for recognizing weeds and assessing plant health. You also have various data mining techniques for optimizing yield, much of AI robotics including autonomous swarms, Large cost savings as well as reductions in pesticide and fertilizer use are projected.

Banking

As banks, financial services providers and brands predict and plan for the way consumers will manage their money in the future, artificial intelligence (AI) is high on the business development strategy.

Smart machines and technology can turn data into customer insights and enhance service provisions, bringing the digital experience closer to the human interaction for consumers.

Machine Learning and Banking

Machine learning technology has advanced rapidly over the last ten years, and there are now more flexible and cost-effective solutions that banks can implement, even with their often legacy-burdened IT systems.

Smart machines and technology can turn data into customer insights and enhance service provisions, bringing the digital experience closer to the human interaction for consumers.

The computer analyses new information and compares it with existing data to look for patterns, similarities and differences. By repeating the activity, the machine improves its ability to predict and classify information making it easier to make data-driven decisions.

Banking

As banks, financial services providers and brands predict and plan for the way consumers will manage their money in the future, artificial intelligence (AI) is high on the business development strategy.

Smart machines and technology can turn data into customer insights and enhance service provisions, bringing the digital experience closer to the human interaction for consumers.

Machine Learning and Banking

Machine learning technology has advanced rapidly over the last ten years, and there are now more flexible and cost-effective solutions that banks can implement, even with their often legacy-burdened IT systems.

Smart machines and technology can turn data into customer insights and enhance service provisions, bringing the digital experience closer to the human interaction for consumers.

The computer analyses new information and compares it with existing data to look for patterns, similarities and differences. By repeating the activity, the machine improves its ability to predict and classify information making it easier to make data-driven decisions.

Banking

As banks, financial services providers and brands predict and plan for the way consumers will manage their money in the future, artificial intelligence (AI) is high on the business development strategy.

Smart machines and technology can turn data into customer insights and enhance service provisions, bringing the digital experience closer to the human interaction for consumers.

Machine Learning and Banking

Machine learning technology has advanced rapidly over the last ten years, and there are now more flexible and cost-effective solutions that banks can implement, even with their often legacy-burdened IT systems.

Smart machines and technology can turn data into customer insights and enhance service provisions, bringing the digital experience closer to the human interaction for consumers.

The computer analyses new information and compares it with existing data to look for patterns, similarities and differences. By repeating the activity, the machine improves its ability to predict and classify information making it easier to make data-driven decisions.

The store of the future

Imagine the store of the future: facial recognition technology detects when you walk through the doors. The retailer already has an idea of the type of clothing you like based on past purchases and the parameters you’ve given them, like your height, weight, etc. You stand in front of a mirror and AI technology immediately “dresses” you in an outfit based on your preferences and unique style.

You easily flip through colours and styles without once seeing the inside of a dressing room. You make your decision and a robot brings you your purchase. You thank him or her for it and walk out of the store – no standing in queues to pay. The physical act of paying is completely redundant. The retailer already has your card details and your account has been debited for the purchase. It’s instant gratification on a whole new level.

Benefits

The idea that we could all one day have our own personal shopping assistants and stylists probably excites a lot of us. But how does the retailer benefit from investments in these new technologies?

Waste, inefficient supply chains, poor stock management and products that are priced out of the market are just some of the reasons retailers could be haemorrhaging cash and losing customers.

AI, cognitive computing and machine learning could completely change the game for retailers. When machines learn about demographics, weather patterns, buying trends and GDP growth for a particular area, they can tell a retailer which products to stock and how to price them for maximum sales.

Machines will know that summer clothes will move off the shelves in areas where it starts to get warmer sooner and that the retailer can reduce the price of its winter clothes in that store. However, it might still be chilly in another province, meaning it’s a good idea for the retailer to keep its winter clothing prices unchanged for maximum revenue.