RAG for finance, precise & cited
Let analysts and ops query filings, research, policies and contracts in plain language — with cited, numerically careful answers, access control and audit logging.
What this means for your firm
Finance teams live inside dense documents: filings, research notes, credit policies, ISDA and loan agreements, KYC files. Answers are buried, time is short, and a wrong number is expensive. Keyword search hands back a haystack; analysts need grounded answers.
A finance RAG system answers directly from your approved documents, cites the source, and is engineered to be numerically careful — it surfaces the figure with its context rather than paraphrasing it into something subtly wrong. When the answer is not present, it says so.
We build with access control, audit logging and data-handling boundaries appropriate for regulated financial data — the same production discipline behind our own options-analytics product, OptionsGyani, which reasons over real market data daily. The outcome is faster research with a defensible trail.
What we build
Document Q&A
Plain-language answers from filings, research, contracts and policies with citations.
Numerically careful
Surfaces figures with their source and context to avoid subtly wrong paraphrases.
Contract search
Pinpoints clauses across agreements and flags where terms differ or conflict.
Access control
Per-desk and per-document permissions so sensitive material stays restricted.
Audit logging
Every query and source returned is logged for compliance and review.
Freshness pipeline
Re-indexing so new filings, notes and policy updates are searchable immediately.
Implementation details
| Capability Parameter | System Specification |
|---|---|
| Sources | Filings, research notes, contracts, credit and compliance policies, KYC files |
| Retrieval | Hybrid vector + keyword search with reranking; table-aware extraction |
| Grounding | Source-cited answers with abstention; figures kept in context |
| Governance | Per-desk access control, audit logging, regulated-data boundaries |
| Studio proof | We run OptionsGyani, a live options-analytics product over market data |
| Typical budget | ₹25L–₹50L / $25k–$60k per production system |