Use this when

Requests arrive in inconsistent, incomplete forms and every downstream step wastes time chasing missing details.

The pattern

REQUEST ARRIVES (any channel)
        ↓
STRUCTURED INTAKE
required fields, validated, choices where possible
        ↓
CONSISTENT RECORD → workflow proceeds on reliable fields
        ↓
DOES NOT FIT? → route to a person

Why it works

The workflow's reliability is capped by the quality of its input. By turning messy, varied requests into consistent structured data at the very start, every later step, human or automated, can trust what it receives. Fixing the input once is cheaper than fixing its effects everywhere downstream.

Two ways to build it

  • A reliable intake form that captures structured fields directly from the requester.
  • An AI extraction step that reads unstructured input, an email or a document, and produces structured fields, followed by validation. See extract then validate.

Good fit

  • High-volume requests where small inconsistencies add up.
  • Workflows where downstream steps need specific fields to decide.
  • Situations where missing information is the main source of delay.

Poor fit

  • Genuinely varied requests that cannot be reduced to fields without losing meaning.
  • Very low volume, where a person handling each one is simpler.

What this does not solve

Structured intake improves the input; it does not verify the input is true. A form can be filled in confidently and wrongly. Validate the fields that matter, and keep a route for the unusual cases.