The insightful articles, inspiring narrations and analytical perspectives presented by the Editorial Team, establish an alluring connect with the reader. My compliments and best wishes to SP Guide Publications.
"Over the past 60 years, the growth of SP Guide Publications has mirrored the rising stature of Indian Navy. Its well-researched and informative magazines on Defence and Aerospace sector have served to shape an educated opinion of our military personnel, policy makers and the public alike. I wish SP's Publication team continued success, fair winds and following seas in all future endeavour!"
Since, its inception in 1964, SP Guide Publications has consistently demonstrated commitment to high-quality journalism in the aerospace and defence sectors, earning a well-deserved reputation as Asia's largest media house in this domain. I wish SP Guide Publications continued success in its pursuit of excellence.
FN Herstal and Cervus Defence & Security are pleased to announce the signing of a Memorandum of Understanding (MoU), marking a significant milestone in the development of their collaboration centred on cutting-edge military training technologies.
Under this agreement, the two organisations will deepen their technical cooperation and align their strategic objectives in the field of small arms marksmanship training.
The partnership brings together advanced FN® E-NOVATION weapon sensors and measurement optics with Cervus' Xcalibr™ platform, a data analysis solution designed to support marksmanship training throughout the entire training lifecycle.
By combining their complementary areas of expertise, FN Herstal and Cervus aim to deliver innovative training solutions that are both more integrated and more data driven, dramatically enhancing user performance at every stage of the training process.
This collaboration reflects the shared commitment of both organisations to responsibly enhancing warfighter lethality, effectiveness and operational readiness through innovation, technological integration and training grounded in objective data analysis.
