Financial ServicesLLM Application

Proprietary Risk Framework Assessment — RAG Over Fine-tuning

RAG POC ~$40K vs ~$300K fine-tuning path — same validated quality band, overnight framework updates.

Build cost

~$300K (fine-tuning)

~$40K (RAG POC)

Framework update time

2-3 weeks retraining

Overnight re-index

Output quality (validated set)

Baseline target

Within accepted tolerance

The Problem

A financial services firm was evaluating an ~$300K fine-tuning project to encode proprietary risk frameworks across multiple scoring dimensions.

The Solution

A short RAG POC over existing risk documentation that matched the proposed fine-tuned quality at a fraction of the cost, with daily re-index updates instead of retraining.

Business Impact

Budget that would have gone to fine-tuning funded a second use case. Risk frameworks update when policy changes — same week, not next quarter.

RAG vs fine-tuning guide

Tech Stack

RAG pipelineClaude 3.5 SonnetPostgresLangChain

More case studies

View all

Crypto / FinTech

Durable AI Ops Layer on Multi-Venue Exchanges

Desk copilots that turn natural-language intent into HITL-approved exchange orders — Vercel AI SDK, Temporal, and MCP — without YOLO trading bots.

Banking / FinTech

Conversational Rules Engine for Crypto↔Fiat Banking

Users set salary-day and balance rules in chat; Temporal workflows execute convert → transfer recipes with confirm cards and zero double-pays on webhook retries.

Banking

Durable AI Ops Layer for Mid-Market Banking

KYC exceptions and payment repairs on Temporal + Vercel AI SDK + MCP — maker-checker Signals, PII redaction, zero double-posts on core retries.

Want a system like this?

Tell us the workflow. We'll reply with a realistic architecture brief — stack, gates, and timeline — not a fantasy ROI slide.