🧭 NEXT GENERATION NAVIGATION FOR HEAVY INDUSTRY STO EVENTS & COMPLEX PROJECTS!

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primavera™ p6 for next generation navigation

Oracle® Primavera™ P6

Oracle® Primavera™ P6 scheduling software is the most widely used application in construction and project management worldwide, surpassing MS Project®; however, its build-in Gen X and Y deterministic algorithm engine for leveling resources does not currently employ Ai augmentation. Furthermore, it was not designed for navigating heavy industry asset intensive regulatory maintenance events or complex projects, and there is no Generation Alpha plan to develop NextGen-Navigation in current or future revisions by Oracle®. We believe our solution will eventually lead to an acquisition.

Agile Scheduling Methodology

Humans engage with scheduling software to code and configure the program, enabling its mathematical algorithm engine to execute scheduling functions for effective and efficient navigation of multi-million-dollar maintenance events and projects worldwide. Human intelligence plays a crucial role in coding, relying on their assumptions and experience. The program does not utilize Generative AI and does not incorporate any aspects of Ai Augmentation (Generative Ai) or Machine Learning. It's time for the next generation of Ai-augmented scheduling to advance agile scheduling in heavy industry!

Mathematical Algorithm Engines

Scheduling software that integrates mathematical algorithm engines with human interaction has significantly improved the creation of optimized schedules and manageable plans in heavy industry for three generations. This advancement has facilitated the navigation of complex, risky, and dynamic maintenance events and projects across diverse industries globally. It is now time for the next generation to emerge, introducing AI augmentation to enhance existing algorithm engine models. 

Machine Learning

Generative Ai and Ai augmentation enable algorithmic engines to learn and optimize scheduled activities and resources while mitigating risks and suggesting alternative solutions to emerging issues in real time. These systems will continue to learn, enhancing their ability to mitigate risks and optimize activities and resources beyond the capabilities of human intelligence, even when employing various agile scheduling methodologies available today.  


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