AI & ML News

CitiusTech Unveils Healthcare’s First End-to-End Generative AI Quality Solution

CitiusTech

CitiusTech’s Gen AI Quality & Trust solution ensures reliability and trust in Generative AI apps, enabling confident enterprise-wide adoption

CitiusTech introduces pioneering Gen AI Quality & Trust solution for healthcare. It ensures reliability, quality, and trust in Generative AI applications, aiding design, development, integration, and monitoring. Boosts confidence for enterprise-wide adoption and scalability.

“We are working with many clients on Gen AI solutions. But we find that over 80% of Gen AI proofs of concept and initiatives are delayed due to reliability and compliance concerns, due to lack of trust in Gen AI solutions. This is the pain point we are trying to solve for our customers, and the healthcare industry at large.” said Rajan Kohli, CEO, CitiusTech.” 

We are working with many clients on Gen AI solutions. But we find that over 80% of Gen AI proofs of concept and initiatives are delayed due to reliability and compliance concerns, due to lack of trust in Gen AI solutions.

Rajan Kohli, CEO, CitiusTech

Our solution offering is a software-based framework coupled with consulting, implementation, and support services. It leverages a state-of-the-art automated design & decision-making framework that will provide pre-packaged measures, automated output validation and monitoring the quality and trustworthiness of Gen AI solutions. 

“At present, there are no established technology or platform agnostic solutions that measure quality and trust of healthcare Gen AI solutions, end-to-end. Approaches used in building and evaluating LLMs, and foundation models are useful, but have not been designed for healthcare,” said Sridhar Turaga, SVP – Data and Analytics, CitiusTech.” 

CitiusTech’s Gen AI Quality & Trust Solutions fully integrate into existing MLOps, DataOps and Quality Management Solutions, and anchors to healthcare use cases and outcomes. Organizations can leverage our healthcare-specific repository of 70+ metrics, 25+ methods across 7 dimensions – Accuracy, Calibration, Robustness, Fairness, Bias, Toxicity and Efficiency. Multiple clients and Healthcare innovators have beta-tested this approach, which has helped shape this offering. 

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