Conversational AI for Financial Services
Retrieval-grounded conversational AI for regulated finance — it answers from your documentation, cites the source, and declines rather than guesses.
Results
The Problem
Client-facing teams field the same questions continuously — product details, process steps, account mechanics, documentation requirements. The answers exist, scattered across internal documentation, and staff time goes to retrieval rather than judgment. Accuracy matters more than in most domains: a confidently wrong answer in a regulated context is worse than no answer.
What We Build
A retrieval-grounded conversational system answering from the organization's own documentation rather than model priors — responses cite their source, and the system declines rather than speculates when the source material doesn't cover the question. Deployed with role-based access so different user groups see only what they're entitled to.
Outcome
- ◆Answers grounded in and traceable to source documentation
- ◆Routine inquiries handled without pulling client-facing staff off higher-value work
Techniques
- ◆Retrieval-augmented generation
- ◆Document ingestion pipeline
- ◆Citation and grounding enforcement
- ◆Role-based access control