Adopting intelligent capture is risky if you don’t have all the facts. Here is actionable advice for avoiding the pitfalls and ensuring project success.
How Cognitive Classification Differs from Rules-based Classification
Cognitive classification is one important intelligent capture application, but it differs from other types of classification: find out how & why it matters.
Why “Machine Learning” Is Not the Answer
Why machine learning is not the only answer and how to find the best solution to meet your organization’s document automation needs. Find out more here.
Is Machine Learning All the Same?
Is Machine Learning all the same? Let’s delve into the most common machine learning techniques, explore how they are used and where.
Automation: What Is Cognitive Capture?
What is cognitive capture? These capture solutions use artificial intelligence or its subset machine learning that have the ability to learn. Find out more.
AI & IA: What Does Intelligent Automation Really Mean?
What does it mean to apply intelligent automation? How is it different from any other automation? Find out in this article.
Don’t Just OCR Documents, Interpret Them | Unattended Automation’s Hidden Role
Don’t just OCR documents. Interpret them. Find out how document interpretation is central to cognitive document automation for the digital workforce.
AI at Your Organization: Deploy or Not to Deploy
Artificial intelligence (AI) at your organization: if AI won’t improve your organization should you deploy it? Find out if, when and how here.
Google, Amazon, Microsoft & Advanced Capture: OCR Software or Something Else?
Google, Amazon, Microsoft & Advanced Capture: are these comparing apples to apples? Article explores differences between OCR software and advanced capture.
Document Automation: Applied Machine Learning Platforms vs Generic ML Platforms
Document automation applied machine learning (ML) platforms are running up against generic ML platforms: how do they compare? Trade-offs considered here.
Machine Learning & Its Voracious Appetite | Machine Learning Primer
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: Blending Best of Humans and Machines
AI is everywhere and not a person to think. This article delves into how AI can be best used in collaboration with humans.