Why basic RAG can fail on deal research questions
Standard , or RAG, often works by cutting documents into small token chunks and using to find text with similar meaning. That can be enough for simple question answering inside a normal business tool. It becomes weak in private equity and M&A work because the useful evidence is spread across many connected places.
A single answer may depend on a banker deck in email, a Slack discussion, an memo in , and an expert interview in a CRM. A question such as what people said about a target company's main competitor during a diligence call two years earlier cannot be answered from one isolated text chunk. A standard may return a few roughly related document links, but it does not understand time, source history, or clear links between people, projects, documents, and decisions.
This is why are being presented as a better fit for work where relationships between facts matter as much as the facts themselves.
Key points
- Basic RAG often splits documents into token chunks and searches for similar text.
- That setup can work for simple internal Q&A.
- Private equity data can be scattered across email, Slack, , and CRM systems.
- Multi-hop questions need links between people, projects, documents, dates, and decisions.
- are useful when the relationships between facts must be searched directly.