Addressing machine learning and its voracious appetite for data requires feeding it volumes of quality data–a primer on types of ML and the data they need.
AI is everywhere and not a person to think. This article delves into how AI can be best used in collaboration with humans.
Here is our assessment last year’s predictions and our tee-up of 2019 predictions and trends that will shape automation and capture this year.
Artificial intelligence (AI) combats voter fraud via new avenues. Signature verification automation powered by AI offers new levels of accuracy and speed.
Machine learning forces a significant shift in how software solutions are evaluated, compared and acquired. Discover the latest in AI for advanced capture.
The practical applications of Deep Learning and its impact on document automation promises to accelerate change in business processes. Find out how here.
If there’s a knowledge base, chances are it is not real machine learning. Find out how to discern between what’s real machine learning and what’s simply an expert system leveraging knowledge bases and human SMEs.
For document automation self-learning software spells the end of vendor feature wars so that businesses can focus on the outcomes; find out why here.
Digital transformation, its impact on the industry and how self-learning software promises to accelerate change in document workflow processes are all discussed in this exclusive interview.
Natural Language Processing or NLP helps make document automation highly successful for certain tasks and fails miserably in others that are explored here.
Tackling more complex processes leveraging enterprise Robotic Process Automation (RPA) requires overcoming some significant challenges. This article explores how to meet those challenges.
Drilling into cognitive robotic process automation (RPA) reveals document automation at its center. This article focuses on cognitive RPA and what it means to your business.