DANATEQ, a leading cognitive streaming analytics company, announced the upcoming release of a new software product called ALEX. ALEX is Auto Learning Engine X.

In a time where analytics, machine learning, and artificial intelligence are keys to gaining competitive advantage across all industries, companies have realized that building such capabilities does not end with deploying technology. Organizations discover that a lot of investments need to be made on its people also. Successful implementations and rollouts of machine learning capabilities are seen in enterprises with big and mature data science teams. An organization’s data science team is key in optimizing and accelerating the output of a typical machine learning software.

Enter ALEX, the self-tuning and self-optimizing AI engine. ALEX removes the need for data scientists to tune predictive models. With ALEX, companies can generate predictions and decisions by simply integrating data sources. ALEX will do the rest.

While DANATEQ has successfully introduced innovations in applying machine learning to big enterprises’ common business problems with its current products, ALEX makes machine learning accessible and relatable to a broader market that could not take on the usual operational overhead, and just needs results.

“Be it a large company, a small enterprise, or even an app developer, all of DANATEQ’s customers shall benefit from the predictive power and simplicity of ALEX”, says Cody Martinson, CEO at DANATEQ, “We are very excited to bring this plug-and-play AI technology to the market”.

ALEX is now available to select customers for beta testing. It will be officially released to the market in Spring 2018. To learn more, please visit www.danateq.com or email contact@danateq.com to request a demo.

ABOUT THE COMPANY

DANATEQ is a leading cognitive software provider headquartered in Singapore. The company’s cognitive systems have been deployed in all continents, and have enabled major companies and business conglomerates to conduct business more effectively through AI and machine learning.