Decision Makers Ltd.
Established in 2008 and headquartered in Shoam, Israel, Decision Makers is dedicated to helping water utilities all over the world detect abnormal water quality event detection without having to invest in additional infrastructure. Because Decision Makers offers its solution as a service, it is able to keep prices low so that water utilities of all sizes can benefit from this technology. Decision Makers Ltd. focuses on transforming data into knowledge, by combining new proprietary algorithms with reliable public-proven algorithms into easy to use, low-cost software components. Our application-specific components for event detection, optimization, and numerical prediction allow our users to focus on what and not on how.
Company details
Find locations served, office locations
- Business Type:
- Software vendor
- Industry Type:
- Water Utilities
- Market Focus:
- Globally (various continents)
- Year Founded:
- 2008
- Employees:
- 1-10
- Turnover:
- less than $1,000,000 US
About Us
- Implement Data Mining and Machine Learning into your Water Systems.
- Decision Makers Ltd uses IBM cloud infrastructure to support its customers.
Decision Makers Ltd is a privately owned company, focusing on developing data mining and optimization tools, allowing researchers, students and developers to utilize highly customizable tools, applicable for a variety of fields.
How it Works
Scalable & Affordable
- Mindset Detector is a cloud-based service.
- Suitable for all water utilities.
- No upfront investment.
- Payment is made on a monthly basis.
- Pay per running model.
- Guidance and calibration is included
Event Detection
Abnormality detection in water is much like detecting credit card fraud.
What is your Gain?
The gap between the detectors’ thresholds and regulation limits gives the water utility the option to react ahead of time.
Mindset Detector
is constructed of logical components called “Detectors”. A detector is an algorithm, which is trained to detect a specific abnormality in data.
Machine Learning
A detector that raises alarms when required is considered more reliable over time, and its alarms gradually receive a higher priority.
Spatial Model
The special model detects abnormalities when the measurement in a station deviates from the expected value, computed according to the water quality at the origin station.
