Vinda chooses ADAMS, by Syntrino Solutions.
Born in 1985 with the philosophy that a “healthy lifestyle starts with Vinda.”
Vinda has always been about providing healthy hygiene products.
Today it counts ten key brands, and operations in over 14 countries like China, Hong Kong, Macau, Malaysia, Taiwan and South Korea.
The Vinda vision – become the leading hygiene company in Asia! by improving the industry, customers and the environment one wipe, sneeze and ah-choo at a time.
In 2018, Vinda decides to partner Syntrino Solutions Sdn. Bhd. with the aim to streamline its supply chain management, sales data, and distribution management system in the region.
Industry leader in Business data intelligence, Syntrino Solutions’ mission is to empower businesses to stay competitive through connected information technology and innovative distribution channels.
With ADAMS, its proprietary advanced distribution and analytics management system, Syntrino Solutions offers its clients across Malaysia and the region the best in business data intelligence, integrating AI and machine learning.
Built today to meet the challenges of tomorrow, ADAMS provides a platform enabling businesses across the region to better manage their operations.
In just a few clicks, it allows businesses to collect, analyze and visualize their data for better decision-making.
- Faster data for simplified decision making.
- No more downtime.
- No more mistakes.
- More control over your operations and stocks.
- A bird’s eye view of the competitive landscape.
- Real-time inventory. Zero lag time reports.
What’s more? ADAMS only works with the best in the world, Tableau, Microsoft Azure, Alteryx, Amazon, SAP Business one.
Facing business operational issues? Lost in a sea of data? No clear direction? Lacking harmonization?
Join Vinda in ensuring flawless operations and faster decision making with the best Business data intelligence management system in the region.
Contact us for more information about how to transform your business through data visualisation, AI and machine learning.
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