Enterprise AI Agents · Measurable ROI · Production Systems

AI agent case study financial services

How a mid-market financial services group cut document review time 78% and reclaimed $180K annually with a DigiAI.pro AI Agent system.

Buyer
CFO · CTO · COO · VP Operations · Head of Technology
Company
$2M – $30M revenue · 20 – 200 staff
Industries
Financial Services · Professional Services · Construction · Manufacturing
The Deployment

This AI agent case study financial services leaders keep asking about is our compliance triage engagement — the clearest example of what a production AI Agent stack looks like on the P&L. A mid-market financial services group was running a 5-person manual review queue processing hundreds of regulatory filings per week, averaging 12 minutes per triage and 36 hours to first response on high-priority items. DigiAI.pro deployed a multi-agent pipeline over 8 weeks: a classifier agent assigns category and risk, a summariser agent produces a 3-line brief, and a router agent routes to the correct officer with justification. A deterministic guardrail layer escalates any low-confidence item to a human — nothing auto-routes below threshold. An evaluation harness re-scores 100 random filings weekly against human reviewers to detect drift before it matters. Triage time dropped to under 90 seconds. Response time on high-priority filings fell from 36 hours to under 4. Zero compliance incidents in six months of production. Roughly $180K in staff cost recovered annually and 40 hours per week reclaimed for actual investigation work. If your compliance queue looks like this, we start with a 30-minute diagnostic.

Proof
78%Document review time reduction · $180K annual recovery

DigiAI.pro is not affiliated with other companies using the name DigiAI. We build production AI Agent infrastructure for enterprise CFOs, CTOs, and COOs — not chatbot or coaching automation tools.

INITIALIZE

Map your highest-ROI AI use cases.

Book a 30-minute diagnostic. We'll identify your three highest-ROI AI Agent opportunities — with projected headcount impact and a deployment timeline. No obligation.