BY Fast Company 2 MINUTE READ

TELL US ABOUT GENII
Genii is a software service company that develops artificial intelligence (AI) and machine learning solutions for Top 500 companies in the financial services, telecommunications, healthcare, insurance, automotive and retail sectors. It was started five years ago as a research and development company. Currently, the company has 55 staff, including business analysts, data scientists, data engineers and software engineers.

WHAT IS YOUR BUSINESS FOCUS?
Genii focuses on providing artificial intelligence solutions. We help B2C companies improve customer service (CX), sales and customer retention. We’ve assisted a number of companies to retain customers through the use of effective AI. 

We once worked with a company that was experiencing challenges coping with the huge volume of calls coming  in to its call centre. Using historical data, we were able to predict what kind of services would be required and who was likely to call and when. This enabled the company to better manage its call centre and to create a better customer experience. Over the past five years, we have assisted companies to achieve different business benefits. The Genii AI model predicts future customer service needs and interactions. It provides a list of who will call, why they will call and when. This enables a company to launch a proactive customer service, thus reducing the need for customers to call the call centres. This results in massive cost savings for the company and improves customer satisfaction at the same time.

WHAT IS THE KEY BUSINESS RESOURCE WHEN DEVELOPING AI SOLUTIONS?
As they say, data is oil, data is our key resource. AI needs data, and in some cases large quantities, depending on the models. Different AI models will need different data sets. Data engineering for AI in most cases is more time consuming than developing the actual algorithms.

WHAT CHALLENGES DO YOU EXPERIENCE IN DEVELOPING AI SOLUTIONS?
Although data access can be a barrier to AI, it is becoming less so with the advent of AutoML. We now have algorithms that better prepare data to reduce human effort. Another challenge is skills to enable the development of AI solutions. We need data scientists, visualisation engineers, business analysts and software engineers to do what we do. It is also still early days for AI; as a result, people are still reluctant to use it.It takes time, data and failure. All of these factors contribute to some of the challenges experienced in developing AI solutions.

ANY ADVICE TO OTHER BUSINESSES?
In order to enable AI and prediction analytics, companies need to have the correct data to feed the platforms. This could be structured and or unstructured data. When predicting future consumer behaviours, a company needs at least historical customer data for a defined period ie POS, CRM, billing, interaction data, etc.

Visit geniianalytics.com for more info.