LlamaIndex

Agentic workflows are only as good as the context they're given, and in finance that context is locked inside the messiest documents you own. Credit memos, audited financials, and credit agreements are where the real risk hides: nested tables, footnoted adjustments, covenant grids, and contingent liabilities buried in the notes. Most document tooling flattens exactly the structure that matters, so what reaches your systems and your agents is already degraded.

In this session, we run a real, dense financial document through parsing and extraction, live. You'll see it come back as clean structure, with the figures and terms that drive the decision pulled into a defined schema, each carrying a page-level citation you can click straight back to the source. Then we check the extracted values against your policy rules, flag anything out of bounds with its source, and finish on a second document with a completely different layout, handled with no rework.

Test

**What you'll see**

*   Dense financial tables and footnotes parsed without losing structure
*   Schema-driven extraction with page-level citations and per-field confidence
*   Extracted values checked against policy, with breaches flagged and sourced
*   Works across different document formats with no per-template setup
