Tripartite MoU Aims to Advance AI in Healthcare

Tripartite MoU Aims to Advance AI in Healthcare

MUMBAI — Findability Sciences Private Limited, Nath School of Business & Technology, and MMRI Kamalnayan Bajaj Hospital have signed a tripartite memorandum of understanding (MoU) to collaborate on the research, development and deployment of artificial intelligence-driven healthcare solutions.

The agreement establishes a framework for building and validating AI applications across areas including clinical decision support, diagnostics augmentation, predictive analytics, operational optimisation and patient outcomes. The partners said the initiative is intended to combine enterprise AI capabilities, academic research and clinical environments to develop solutions that are scalable and compliant with ethical standards.

Under the MoU, Findability Sciences will lead AI architecture, model development and governance using its enterprise AI frameworks. Kamalnayan Bajaj Hospital will provide clinical expertise, anonymised healthcare data in line with statutory and ethical norms, and access to clinical environments for testing and validation. Nath School of Business & Technology will contribute faculty expertise, research support and student participation for applied research and documentation.

“Healthcare AI must be built where decisions are made—at the intersection of data, clinicians, and real operational constraints,” said Anand Mahurkar, Founder and CEO of Findability Sciences.

Dr. George Noel Fernandes of MMRI Kamalnayan Bajaj Hospital said the collaboration aims to translate clinical and operational data into actionable intelligence while maintaining patient trust and ethical standards.

Harsh Vardhan Jajoo, Director of Nath School of Business & Technology, said the initiative will enable faculty and students to work on real healthcare challenges and applied AI solutions.

The partners said the collaboration will also allow for publication of non-confidential research findings, subject to intellectual property and confidentiality provisions.