Splitting a long document into AI experts to cut costs
A 700-page document is handled by splitting it into separate “” instead of putting the whole document into one large . After a PDF is uploaded, each document section becomes its own expert with its own context and reasoning. Several experts can be grouped under one , which sends each question to the right expert.
Questions that need information from several sections go to multiple experts, and their answers are combined into one response. The system is exposed as an . One example is turning company knowledge from legal, finance, HR, and product teams into separate experts, then querying them together as one company .
It claims to work without a , , or a retrieval step. It also claims to be 70-90% cheaper than loading everything into one .
Key points
- A PDF is split into section-level .
- An routes each question to the right expert.
- Questions spanning multiple sections can call several experts and merge the answers.
- The system claims no , , or retrieval step is needed.
- The claimed cost saving is 70-90% compared with loading everything into one .