How to Measure Employee Productivity Without Micromanaging
Jul 15, 2025 in Guide: How-to
Learn how to measure employee productivity with methods that build trust. Discover modern metrics, tools, and strategies to foster growth, not fear.
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How to Measure Employee Productivity Without Micromanaging
Jul 15, 2025 in Guide: How-to
Learn how to measure employee productivity with methods that build trust. Discover modern metrics, tools, and strategies to foster growth, not fear.
Read MoreNov 29, 2021 in News
This article describes the key points of my participation at the 2021 Edition of the World Data League. The Tech Moguls Team, composed of me, Tiago Gonçalves, Tomé Albuquerque and Joana Morgado, from INESC TEC, finished second place in this edition. World Data League (WDL) is a Data Science competition where groups of Data Scientists […]
Nov 9, 2021 in Use Case
In this article, we will cover a use case in the construction industry related to forecasting the needed materials for construction and the time in which they will be required. In the construction industry, there is a lot of uncertainty between the order time and the time in which it is actually executed, due to […]
Oct 1, 2021 in Use Case
During recent years Artificial Intelligence has been applied to almost all domains and industries to improve or solve specific problems identified by humans. One example is the industry of Food and Beverages, where AI models are being used for different purposes: Finances: by creating more predictable demand forecasts. Innovation: by suggesting new ingredients combination and […]
Aug 2, 2021 in Technical
The Miranda warning prevents us from self-incrimination. You have the right to remain silent. Anything you say will be used against you. If we hold ML models accountable for their predictions, shouldn’t we at least grant them that right? Can we expect ML models to know everything? I guess we don’t! Moreover, it would be […]
Jul 27, 2021 in Use Case
Having access to liquidity has been a major issue for humankind for financing both personal life aspects (e.g., housing, cars, college) and for business initiatives (e.g., starting, growing, and expanding a business). The amount of uncertainty that both faces of this exchange – i.e., the creditor and the prospective debtor – face are paramount. On […]
Jul 17, 2021 in News
We are proud to announce that NILG.AI was among the winning startups of the 4th open call for the DataHub Ruhr. DataHub Ruhr is an open innovation initiative that creates matchmaking opportunities between major corporations in the Ruhr area and global startups. In the 4th edition of this program, 8 challenges were proposed by 4 […]
Jul 14, 2021 in Use Case
NILG.AI, together with Neu.ro decided to try a format similar to a Reading Club, where the topic is not a specific paper but an entire research area. After a short discussion, we had a System Design part where the team described a specific use case to apply the new approach. Ideally, the discussion would stick […]
Jun 14, 2021 in Use Case
When we decide to buy or rent a real estate (apartment, room, house, etc), one of the most important search criteria is the price. Its value depends mostly on characteristics, such as location, year of construction, number of rooms, area, central heating, etc. However, two properties with the same characteristics, for example, can be sold […]
Jun 1, 2021 in Industry Overview
At NILG.AI, our motto is “Unlocking business capabilities using Data Intelligence”, since we see Artificial Intelligence as a powerful tool designed to maximize the potential of human activity. A lot of fields have been taking advantage of the AI revolution creating more efficient systems able to get more accurate results while saving time and operation […]
May 18, 2021 in Technical
Multiple Instance Learning (MIL) is a form of weakly supervised learning where training instances are arranged in sets, called bags, and a label is provided for the entire bag, opposedly to the instances themselves. This allows to leverage weakly labeled data, which is present in many business problems as labeling data is often costly: Medical […]
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