Cited answers from your filings, contracts, and policy — not a model's best guess at the regulation.
Financial teams reason over documents that are long, structured, and unforgiving: 10-Ks, prospectuses, ISDA agreements, credit memos, and shifting regulatory text. A base model invents plausible figures and misreads a footnote, which is a reportable error rather than a rough draft. The cost of a wrong number here is not a bad answer — it is a compliance finding.
Analysts stop parsing 1,000-page filings by hand and query them in plain language
Every answer carries a citation, so compliance can audit the source in one click
Citation confidence high enough to stand behind in a regulated workflow
New filings and policy versions enter the corpus without re-architecting retrieval
Yes. We use multi-stage parsing and parent-document retrieval so nested tables and cross-page footnotes survive chunking — a single misread decimal in an SEC filing is treated as a failure to engineer out.
Every answer is constrained to retrieved passages and cited back to page and section, with a verification pass before it surfaces. For Finance-Mind this reached 99% citation confidence and cut manual research time by 92%.
No. Generation is grounded only in what retrieval returns from your corpus, with self-checks that block answers the sources do not support — no external leakage into a regulated response.
