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How EY can Help
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A managed care company saves hundreds of hours in compliance verification with a new, AI-enabled database. Learn more in this case study.
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Streamlined grant application
Opportunity: State governments often face the challenge of accurately identifying suitable federal health grant opportunities and creating compelling funding proposals. The traditional approach to grant search and application drafting is resource-intensive and time-consuming, with the potential for inaccuracies and missed opportunities.
Solution: Leveraging large language models (LLMs) simplifies the grant application process, offering a two-fold solution. Firstly, by extracting key concepts from grant opportunities, matching them with relevant health factors based on generated relevance scores. Secondly, by automatically generating draft grant applications using function-specific models and prompts, increasing output quality and reducing error.
Outcome: This solution can significantly streamline the grant application process, saving both time and resources. It ensures the accuracy and consistency of applications, provides customized proposal content, and garners insights from past applications to inform future strategies. Uniquely, this model also enhances the state government's capacity to secure funding and address community needs, fostering improved community services and welfare.