On Friday, shares of Zen Technologies, a company that provides defense training solutions and anti-drone technology, increased by more than 4% after the company told exchanges that it had received an order from the Ministry of Defense worth Rs 152 crore.
Compared to the previous closing of Rs 1,466.15, the counter opened in the green at Rs 1,482. The stock continued to rise, reaching a peak of Rs 1,529 on the BSE. The counter was up 1.35 percent at Rs 1486 when it was last seen.
The counter has a 52-week high of Rs 2,627.95 and a 52-week low of Rs 886.20. The company’s market value is Rs 13,417 crore.
The information provided indicates that the order is for the provision of its virtual simulation system, which will offer thorough training for air defense operations.
According to a corporate release, Zen will supply its proprietary Integrated Air Defence Combat Simulator (IADCS) as part of this deal.
Zen IADCS is a virtual simulator that provides realistic war scenarios and improved realism in weapon control for training L 70 and ZU 23-2 gun crews.
“Believing in the transformative potential of this simulator, we independently invested in its research and development. “With its successful introduction, we anticipate a great deal of interest from friendly foreign countries that operate legacy air defense platforms like the L70 gun, as well as from within India,” stated Arjun Dutt Atluri, vice president of Zen Technologies.
Zen Technologies Share
The stock has produced a multibagger return of 644% in three years and 400% in two. It has provided a staggering 5,750% return in just 5 years. But thus far this year, it has corrected by more than 38%.
The company previously unveiled the AI-powered robot Prahasta, among other items, for the worldwide defense industry in partnership with its subsidiary AI Turing Technologies.
Prahasta is an automated quadruped that understands and produces real-time 3D terrain mapping for unmatched threat assessment, navigation, and mission planning using LiDAR (light detection and ranging) and reinforcement learning.
