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Case study · Document pipeline

Document pipeline automation for a fintech operations team

An OCR → extract → reconcile pipeline with a full audit trail, replacing a four-person manual document operation.

12k
documents processed per day
client Fintechindustry Financial servicesteam ~60 staff, 4-person ops team on documentstimeline 10 weekscodename Ledger
01 · Problem

A 4-person ops team, all day, every day

The company processed 12,000 vendor documents daily — invoices, contracts, statements. Every document was OCR’d, line-itemized, and reconciled by hand.

  • Throughput was capped by headcount, and volume was growing 8% a month
  • Manual keying produced reconciliation errors that surfaced weeks later
  • Audit requests took days because provenance lived in people’s memories
02 · Why it mattered

The cost of leaving it alone

Document throughput gated revenue: vendors couldn’t be onboarded faster than paperwork could be processed, and error remediation consumed the team’s best people.

03 · Architecture

OCR → extract → reconcile, with an audit trail

Cloudflare Queues feed parallel workers. Tesseract handles clean documents; Claude takes the messy ones. Every extraction is logged and every reconciliation is human-reversible.

  • Two-tier extraction: cheap OCR path with LLM fallback for degraded scans
  • Confidence routing: anything under 0.85 lands in a human review queue
  • KMS encryption at rest with a per-row audit log
  • p95 processing latency of 1.2 seconds per document

Stack: Claude · Tesseract · Cloudflare Queues · S3 · Postgres

04 · Implementation

How it was built

  • Week 1–2: corpus analysis across 40k historical documents; accuracy baseline defined with the ops lead
  • Week 3–5: pipeline built end-to-end on one document type, running shadow-mode against the manual process
  • Week 6–8: remaining document types added; reconciliation rules encoded with finance sign-off
  • Week 9–10: cutover, monitoring, and training the two-person review team
05 · Results

What the numbers say

docs/day
12k
accuracy
99.4%
p95 latency
1.2s
cost/doc
$0.018
06 · After launch

What happened next

Three of the four ops people moved into vendor relations and dispute work — higher leverage, less drudgery. The pipeline runs under a monitoring retainer; quarterly reviews add document types as the business expands.

This system is an example of Workflow Automation & Integrations work.

$ erick --find-bottleneck 

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