https://store-images.s-microsoft.com/image/apps.13778.50b01cbf-976a-41b6-9504-3e206c1b0a62.d593fd5b-95d6-43f9-89d5-262a635e6d8b.491674bd-3598-4be9-a745-725fab331587

Hourglass Insights

Hourglass Software LLC

Hourglass Insights

Hourglass Software LLC

See what your emails are about at a glance using Natural Language Processing!

Hourglass Insights is an Add-in for Microsoft Outlook. Make going through your inbox more efficient! It uses Natural Language Processing Machine Learning to perform two operations on the text body of Outlook emails:
1) Determine the Sentiment of the email
2) Extracts the top two most important phrases in the email
these are determined, add the results in the add-in, so it is clear for the user to see what the “tone” of the email and is what it is about. For example, after analysis, add-in will show:
SENTIMENT: POSITIVE/NEUTRAL/NEGATIVE
KEY PHRASE 1: some key part of the email
KEY PHRASE 2: second key part of the email

Imagine you are at work, or in communication about something important via email. You receive a very long, and important email with complex sentence structures. How you respond will be critical. You could try and slowly read the email and attempt to digest all the content. You also try and gauge the sender's intent. With Hourglass Insights, this will automatically be done for you. It will tell you the sender's "tone" in the email and the top two most important phrases of the email content. Both these factors will allow you to create a response or perform actions that are accurate and successful for the objective. Machine Learning handles the details for you and gives you this information in an instant.
https://store-images.s-microsoft.com/image/apps.43111.50b01cbf-976a-41b6-9504-3e206c1b0a62.d593fd5b-95d6-43f9-89d5-262a635e6d8b.5994fffa-e7a2-4961-88d2-40fade7e9f06
https://store-images.s-microsoft.com/image/apps.43111.50b01cbf-976a-41b6-9504-3e206c1b0a62.d593fd5b-95d6-43f9-89d5-262a635e6d8b.5994fffa-e7a2-4961-88d2-40fade7e9f06
https://store-images.s-microsoft.com/image/apps.38737.50b01cbf-976a-41b6-9504-3e206c1b0a62.d593fd5b-95d6-43f9-89d5-262a635e6d8b.27777ac0-6a3e-41de-b4df-977ccfeb4454