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04 / Legal / AI

Referral Intelligence Platform

Referrals were coming through scanned PDFs, email attachments and intake forms. The intake process depended on staff retyping the same information and checking for missing fields. We built one pipeline that reads, validates and routes every referral.

Legal / AIOCR · n8n · LLM extraction · ClickUp
86%reduction in average intake time
1.3 minmedian processing time per referral
7.2 hrsaverage weekly admin time recovered
What we built

A system designed around the actual work.

  • Automated email and document capture
  • OCR for scanned referrals
  • Client and case detail extraction
  • Missing‑field detection
  • Duplicate referral checks
  • Structured case creation
  • Trackable intake queue
How it works

From input to action through one connected flow.

01

RECEIVE

Capture fax, email or form submission

02

READ

Run OCR and extract required fields

03

CHECK

Detect missing or duplicate information

04

TRACK

Create and route the intake record

Delivery scopeSolution architecture, workflow design, AI integration, application engineering and production implementation.
TechnologyOCR · n8n · LLM extraction · ClickUp
Measured outcome

Operational work became visible, measurable and easier to scale.

Average intake time moved from 9.6 minutes to 1.3 minutes for referrals that passed confidence checks. Exceptions were visible immediately instead of surfacing later in the process.