Manufacturing /Document processing live field guide · 8 min

Order Intake Sorter

Reads inbound customer orders arriving as email text and varied PDFs, extracts them into ERP-ready fields, and flags any mismatch against your item master — landing a clean, reviewable record instead of a re-keyed one.

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theater/demos/manufacturing_order-intake-sorter.html · sandbox · read-only

Open

FIG. 1

The live demo, running on fabricated data. Open it to step through the full flow — every output is shown for a person to approve before anything happens.

How it would work

Reads each inbound order — email, PDF or scan — extracts customer, PO, line items and dates into ERP-ready fields, checks every SKU against your item master, and surfaces the unmatched lines for an order processor to approve before the order enters the ERP.

Input 01

The order, however it arrives

An inbound customer order — a plain-email order, a retailer's PDF purchase order, or a scanned page — plus your item master as the reference list of real SKUs and the units and lead times you actually sell.

Agent 02

Extracts, then cross-checks

Pulls customer, PO number, each line's SKU and quantity, ship date and delivery address into structured fields, then checks every SKU against the item master and flags any that don't resolve to a real, current code.

Output 03

A draft record, flags shown

An ERP-ready draft with each field's source and confidence laid out, the unmatched lines marked, for an order processor to correct and approve before the order is entered into the ERP.

Where it works well

It does the line-by-line SKU cross-check every time, on every order, and shows where each field came from.

Done by hand it is minutes per order plus a 2–3% data-entry error rate — and the error you don't catch becomes a mis-picked or short-shipped order.
Best for an order processor or customer-service team taking orders from multiple customers whose PO formats differ and change without notice.
At a few hundred orders a week the recaptured time goes back into chasing genuine queries and managing the customer relationship, not transcription.

The slow, invisible cost of order entry is the re-keying — reading a retailer's PO layout you've never standardised, finding each product code, and typing it into the ERP without transposing a digit. The check that a code actually exists in the item master is the first thing dropped at peak.

Where it works badly

It is confidently wrong when the item master is stale — the draft looks clean while a discontinued code reads as valid.

Weak on handwritten or low-quality scans, and on free-text orders that describe a product without naming a code — it should flag, not guess at, the match.
If most of your orders are bespoke or made-to-order with no standing SKU, the item-master check has little to match against and gives you less than your own reading does.

The honest test

If you cannot say, right now, that your item master reflects what you actually sell today — discontinued codes removed, customer part numbers mapped — this tool makes your wrong order faster, not safer.

Point it at an item master that still lists last season's SKUs, or one a customer orders against using their own part numbers, and it produces a tidy, professional draft full of codes that map to the wrong product or no longer ship. That is the trap.

What it doesn't do — and shouldn't

It drafts the order record. A person approves it into the ERP. That boundary is deliberate.

WHAT IT DOES

Surfaces each extracted field with the part of the document it came from

Marks every SKU it could not match to a current item-master code

Shows a confidence on each field so low-certainty reads stand out

WHAT IT WON’T

Enter or confirm the order in the ERP

Commit stock, a price, or a ship date to the customer

Decide whether an unrecognised line is a real product or an error

A confirmed order is a commitment that drives production scheduling, stock allocation and what the customer is invoiced — and the item master it checks against is controlled reference data under an ISO 9001 quality system. A wrong SKU or quantity entered unreviewed becomes a mis-build or a short shipment. The accountable person stays on the decision because the consequence lands on them, not the tool.

What your data has to look like

A current item master, and order documents legible enough to read a code and a quantity from.

Typical readiness

across orgs we see, before the first job

An item master that reflects what you sell today

Usual weak point

Customer part-number mappings

Needs shaping

Orders captured as text, not only images

Usual weak point

ERP field mapping

Usually ready

A defined order inbox

Usually ready

The real first job

The item master is usually the weak point — codes that no longer ship, customer part numbers nobody has mapped, units that don't match the order. Getting that reference data current and the customer mappings captured is usually the real first job, larger and more valuable than the extraction layer on top. Once the master is clean, every order after that is faster and right by default.

Right fit if…

You take orders from multiple customers whose PO layouts differ and change

A few hundred-plus orders a week, mostly against standing SKUs

Your item master is current and reflects what you actually sell today

Order entry into the ERP is presently a manual re-keying step

Walk away if…

Most orders are bespoke or made-to-order with no standing SKU to match

Your item master is a stale spreadsheet nobody owns

Orders arrive mainly as handwritten notes or poor-quality scans

You need a tool that confirms orders into the ERP without a person

Open questions

The worried-buyer questions, answered straight

It can extract a wrong line — which is exactly why nothing reaches the ERP on its say-so. It pulls each field, checks every SKU against your item master, and shows its working: the field’s source in the document, a confidence, and a flag on any code it could not match to a current item. An order processor reviews those before approving. The tool surfaces the record; the person commits it.

Layout variation is the case it’s built for — it reads each order on its own terms rather than to a per-customer template. Clean email and digital PDFs extract reliably; handwritten notes and low-quality scans are weaker, and there it flags low-confidence reads rather than guessing. Where a customer orders against their own part numbers, it needs a mapping to your SKUs to match them.

No. It removes the re-keying and the line-by-line SKU lookup so the team spends its time on the judgement: querying an unrecognised code with the customer, confirming a tight ship date is achievable, managing the relationship. The order is still entered by a person. The capacity it frees goes back into customer-facing work, not transcription.

Current to what you actually sell today. The item master is the list every SKU is checked against, and in a manufacturer running an ISO 9001 quality system it’s controlled reference data. If it still lists discontinued codes or omits a customer’s mapped part numbers, the tool validates an order against the wrong truth. The honest test: does your item master reflect this week’s product range?

Customer orders carry commercial information — pricing, volumes, delivery detail — that belongs to you and your customer. Any deployment runs against your own systems and data handling, not a shared pool; we scope where the order data sits and who can see it as part of the build. The demo here runs entirely on fabricated data — Acme Engineering and its PO are invented.

It drafts to the item master and rules it’s given and flags what it can’t match, but it does not certify the order or the entry as compliant. Document and record control sits under your ISO 9001 quality system, and a person confirms the order is right before it’s committed. The tool gets the draft most of the way; the accountable person closes the gap.

What it takes to build

3–4 weeks · 4 phases

Reused from template~70%

Bespoke to this skin~30%

stack · Claude · document extraction · review UI

What it would cost

Fixed scope, fixed price, fixed dates.

Bite-sized first piece

One contained change, low risk

Pilot build

Most builds land here

Embedded support

Scale on proof

Considering this for your order desk?

The honest place to start is a bite-sized first piece — one contained change, low risk. Tell us where it hurts; we'll play it back, scope it, and show you what's possible.

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