Smarter Business from Anywhere at Anytime
Automation technologies have evolved to meet market demands for greatly improved integration of technologies that improve and enhance customer engagement, drive operational excellence and increase business growth. Consolidating "like" automation and artificial intelligence (AI) builds the software framework of a comprehensive Automation Platform.
Tromba Intelligent Automation solution builds upon machine learning to transform structured and unstructured data and documents into actionable insights, and embedded AI smartly recognizes people, content, and context. This results in a powerful workforce combining digital workers with human talent, all without the friction and cost of managing multiple, disparate, separated solutions. The delivered benefits of Intelligent Automation are the lower total cost of ownership with reduced manual work and increased accuracy. An automated business workforce is more productive, and customers are more engaged. The open architecture of Tromba's Intelligent Automation solution allows you to customize your digital transformation and embrace and extend the platform capabilities at the pace that best suits businesses.
The result is a powerful "total" workforce comprising digital workers and human talent—without the friction and cost of juggling multiple, disparate point solutions. Your organization benefits from a lower total cost of ownership and reduced manual work and errors. Your workforce is more productive, and customers are more engaged. And the open architecture of the Intelligent Automation platform allows you to customize your transformation, adopting and extending platform capabilities at your own pace. Your digital transformation journey is unique.
Blog Posts related to Intelligent Automation ...
Videos related to Intelligent Automation ...
Entity extraction automatically—and with a high degree of accuracy—determines which entities are being referred to by the text using both NLP techniques and analysis of information gleaned from contextual data in the surrounding text. For example, is the word “jaguar” referring to a large cat or a car?
Sentiment analysis, in combination with other NLP algorithms, reveals the customer’s opinion about a range of topics—from your products and services or your location to your advertisements or even your competitors. Sentiment analysis is not a once-and-done effort and provides ongoing value.
Using a combination of NLP and machine learning, specific data is found, recognized as valid, and then extracted to be compiled into a data set or for ingestion into a business application. Over time, this process “learns” and can more accurately and efficiently extract data for business processes.