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AI Integration

When a Document Has to Pass Through Five Systems

Multi-step document workflows across intake, extraction, validation, approval and write-back: retryable stages, one state store and daily reconciliation.

Updated 2 min readBy SpiderHunts Technologies

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Quick answer — TL;DR

Make each stage independently retryable, keep state in one place, and make every item traceable end to end. The orchestration is where these projects succeed or become unmaintainable.

The stages

  1. Intake — email, portal, scan or upload, all normalised to one queue
  2. Classification — what kind of document is this
  3. Extraction — the fields, per document type
  4. Validation — against master data and internal consistency
  5. Review — for anything uncertain or consequential
  6. Write-back — into the destination system, idempotently

One place holds the state

Every item has a record with its current stage, its history and its data. Without that, a document that stalls between stages is invisible, and invisible stalls are how trust dies.

That record is also what makes the audit trail possible and what lets a person answer “where is my invoice?” in five seconds.

Each stage independently retryable

A failure at validation should not require re-extracting. Store the output of each stage so a retry starts from the last good point.

It saves cost, it saves time, and it makes incidents far less dramatic.

Design the queues properly

  • Ordered by consequence rather than arrival
  • Age visible and alerted on, so nothing sits unnoticed
  • A quarantine for items that failed repeatedly, with the reason
  • A way to reprocess a quarantined item after a fix

Reconcile daily

Compare what entered intake against what reached the destination, every day. The difference should be explainable in one line: in review, in quarantine, or rejected.

Any unexplained gap is a silent failure, and finding it the same day is the whole point.

FAQ

Frequently asked questions

The questions readers ask us after this guide.

Still have a question?

Ask us directly — a senior engineer will get back to you.

Ask about your project

How many document types can one pipeline handle?

Many, with classification routing to type-specific extraction. Start with one, add the second once the pattern is proven.

What if a document is misclassified?

It should be correctable in review, and the correction should feed back. Misclassification is usually the cheapest error to fix and the most annoying to leave.

Do we need a workflow engine?

Not necessarily. For most business volumes a simple queue and state table is easier to run and easier to reason about.

How long to build?

Six to twelve weeks for a full pipeline with one or two document types, review interface and reconciliation.

Keep reading

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