• Mohit Pagade
• Neha more
• Kunal Bhagat
• Mayur Mahadole
• Prof. Supriya Kulmethe

Proactive AI represents a transformative approach in software development, characterised by its ability to anticipate potential issues and streamline workflows before problems manifest. It integrates intelligent analysis and predictive insights to optimise code quality, accelerate development cycles, and enhance overall system responsiveness. By continuously monitoring project health and adapting to emerging patterns, this technology empowers teams to focus on innovation rather than routine troubleshooting. Proactive AI leverages automation and machine learning to detect inefficiencies, propose improvements, and enable seamless collaboration, ultimately fostering robust, adaptive software ecosystems. This forward-looking capability reduces downtime, mitigates risks early, and drives sustainable development practices that keep pace with evolving user demands and technological challenges. Key Features:  Utilisation of large language models (LLMs) for code analysis  Specialisation nodes for memory search and modification to manage error data and workflow  Detect graph control for explicit monitoring  Safe code execution to avoid side effects during live patching  Continuous expansion, updating and supporting proactive prevention of known issues

"Proactive AI", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 12, page no.c687-c690, December-2025, Available :http://www.jetir.org/papers/JETIR2512280.pdf

"Proactive AI", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 12, page no. ppc687-c690, December-2025, Available at : http://www.jetir.org/papers/JETIR2512280.pdf