According to a Mckinsey survey, 56% of the respondents cited Inaccuracy as the most cited risk of GenAI adoption. This becomes a larger risk for Healthcare organizations who are trying to adopt GenAI into their patient and member journeys as one incorrect decision could have serious impact on their health.

CitiusTech's customizable solution combines consulting and implementation services to design, develop, integrate, and monitor quality and trust - providing the confidence and governance pivotal to scale GenAI initiatives.

Solution Features:

Large coverage: 70+ metrics across Accuracy, Calibration, Robustness, Fairness, Bias, Toxicity & Efficiency

Multiple Methods: 25+ scenarios across Direct prompting, Chain of thought, Meta prompt, ReAct prompt, Adversarial prompt

Readily configured Data sets: 50+ Datasets across SuperGlue, SQuAD, PubMedQA, emrQA etc.

Rigorous Validation: 4 Layers of Trust validation to review output

How does the Solution work?
Design and decision-making framework for GenAI that is healthcare specific. Enables measurement of quality and trust at the level of data, search/retrieval, LLM response, and application outcome​. Monitors GenAI application security and compliance to regulatory frameworks

Value Proposition Efficiency: Automated systems unlock the ability to manage large scale Gen AI deployments with optimized human capital

Ease of Use: Can be integrated with existing workflows as a software library, Intuitive dashboards & inbuilt alerting mechanisms

Traceability: Achieve end to end traceability from Prompts, Responses to Quality measures

Transparency: Reporting metrics, trends, reasons, & evidence to promote adoption

Accelerated Value: Leverage CitiusTech's pre-built software framework to cut down on time, effort and cost.

The AWS tech stack leveraged for this solution are AWS S3, AWS Textract, DynamoDB, AWS Bedrock, AWS Lambda and Kendra Services