AI solution is two folds: 1. use SBERT transformers for retrieval work and 2. use LLM through API with RAG optimization. Where do we use this? 1. Document library - user imports and the model autocategorizes the files into prescribed categories creating an organized library. 2. Fundraising involves due diligence questionnaires ("DDQ") (sometimes 100s of pages) that fund managers need to answer. Our model extracts the appropriate answers from existing database of prior DDQ and also screens all other information about the fund to generate an answer that wasn't drafted before. AI solution is two folds: 1. use SBERT transformers for retrieval work and 2. use LLM through API with RAG optimization. Where do we use this? 1. Document library - user imports and the model autocategorizes the files into prescribed categories creating an organized library. 2. Fundraising involves due diligence questionnaires ("DDQ") (sometimes 100s of pages) that fund managers need to answer. Our model extracts the appropriate answers from existing database of prior DDQ and also screens all other information about the fund to generate an answer that wasn't drafted before.
- Other
No customer case published