Customer: Billion-dollar non-profit research institution
Challenge: Responding to requests for proposals (RFPs) was a time-consuming and manual process
Solution: Platform to quickly find RFP answers and predict which proposals our customer was most likely to win
Our customer, a billion-dollar non-profit institution, funds multinational research from public and private sources by submitting RFPs. To successfully compete for a given RFP, the institution employs a team of proposal writers to source and answer research requests. Each proposal must be tailored to the RFP, which is an arduous process requiring a deep investigation into approaches and methodologies from past successful proposals that are most like a current RFP.
Infinia ML customized our intelligent document processing platform to automatically search through hundreds of thousands of documents from our customer’s past proposals. A user interface was built to allow proposal writers to search and sort through internal proposal documents to streamline their internal investigation. The algorithm also predicts which proposals are most likely for the customer to win based on past work, so the non-profit can focus time and resources on the best opportunities.
Through their new internal enablement platform, our customer decreased manual research times while better assisting proposal writers in the process. This empowered our customer to improve both the quality of proposals and the speed in which they can respond to them. Infinia ML’s solution allows the non-profit to remain lean and pursue high-yield funding opportunities.
Infinia ML built a document processing pipeline to automatically digitize, extract, and normalize information across multiple languages and platforms.
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