When you peruse our newly revamped website, you see overarching tech strategy is the heart of what we do. AI, BI, automation and enterprise software systems designed to disruption-proof your business. But sometimes it’s okay to take a break from all that intensive forward-thinking to make sure you’re getting the most out of what you…
Well, hello there! How productive were you today? Did you create an AI app before breakfast? Take all the data you have access to and apply machine learning to make some huge business decisions? Welcome to the new way to run a business, according to Microsoft. This week, Microsoft hosted its annual Ignite Conference in…
If you were excited about the release of Virtual Entities as part of Microsoft Dynamics 365, you were probably equally puzzled about the limited documentation available. There is virtually (pun intended) no information on integrating Virtual Entities (VE) into a production environment. Many examples online don’t go beyond a “Hello World” integration using the Purdue course API. Fortunately, we have investigated Virtual Entities for a few of our clients and wanted to share our discoveries as to the limitations and benefits.
In keynotes and sessions at Microsoft Ignite 2018, many stories of organizations that are leveraging Dynamics 365 to fundamentally transform the organization to meet the changing expectations of customers were shared. These success stories are compelling, however it begs the question: “what’s the true return on investment (ROI) for an average Dynamics 365 deployment?” Thanks to an independent analysis from Nucleus Research, we can reveal the answer:
We had a lot of fun in Part 1, exploring Automatic Speech Recognition (ASR) and brainstorming ways it can help business harness unstructured data to work smarter. But now we’re moving into the nitty-gritty. What’s technically possible, and who’s currently doing it best?
Most companies are drowning in phone calls, social media posts, emails, audio and video. Like podcasts, all this unstructured data contains good info. It’s trying to tell you something, but it’s trapped in a form that doesn’t easily lend itself to data analysis. Artificial intelligence helps you liberate your data, organize it, and put it to use.
