Sales order OCR software reads an incoming customer purchase order and returns its data as structured fields instead of a PDF somebody has to retype. Upload the PO your customer emailed and you get the buyer, ship-to, requested dates, terms, and every line with SKU, quantity, unit of measure, and price, as a spreadsheet or JSON. That is the capture half of sales order automation, and it is the half that eats your order desk. Drop a customer PO below and see the fields.
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Most B2B orders still arrive as a PDF attached to an email. Every customer formats theirs differently, so the order desk opens the file on one monitor, the ERP order screen on the other, and types. That is where the errors and the lead time come from, and it is the specific step OCR removes.
A distributor with 400 accounts receives 400 layouts. Template based capture means building and maintaining a map per customer, and the map breaks the first time that customer changes their PO form. That maintenance is why template tools quietly stop being used.
Header fields are easy. The item grid is not: merged cells, wrapped descriptions, quantities split across pages, and unit of measure hiding in the description text. Miss a unit of measure and you ship 12 cases instead of 12 each.
When capture is manual, orders are processed in the sequence someone opens them. A same day order that arrived at 4pm sits behind 30 routine ones, and the customer hears about it the next morning.
The established order automation platforms are genuinely good, and they are also implementations with scoping, ERP connection work, and a signed annual contract. If you want to test capture accuracy this week on real customer files, that is a slow way to find out.
This is a document reader, not an order management platform. It turns an unstructured customer PO into structured data your team or your integration can use. It does not write the order into your ERP, chase an approval, or send an acknowledgment. Being clear about that line is the point: if you want the capture step solved today without a project, this is that, and if you want end to end order workflow you want a platform instead.
The model reads layout it has never seen before, so a new account does not mean a new map. Add a customer on Monday and their first PO parses on Monday.
The item grid comes back as rows: line number, customer part number, your SKU where it is printed, description, quantity, unit of measure, unit price, and extended amount.
Native PDFs, scanned faxes, and phone photos of a signed order all go through the same OCR path, which matters because plenty of B2B orders are still scanned.
Take Excel, CSV, or Google Sheets if a person keys the order, or call the REST API and get JSON if your middleware writes it into the ERP for you.
The buyer is almost always an inside sales or customer service manager at a distributor or manufacturer whose team keys customer purchase orders into an ERP by hand. The order volume is high enough to hurt and the customer base is varied enough that templates do not hold. What they want is narrow: stop the retyping, cut the keying errors, and get same day orders in before the cut off. They are not shopping for a procurement system, and they are usually not ready to sign an annual platform contract to find out whether capture accuracy is good enough on their own files.
The document itself is the same object we read on the buy side, just pointed the other way. Your customer raised a purchase order; from where you sit it is a sales order waiting to be entered. That is why the field set overlaps almost completely with a purchase order parser, and why the part that decides whether the output is usable is the item table rather than the header. If the grid is wrong, the order is wrong, which is covered in detail in purchase order line item extraction.
Once the order is structured, the destination decides the format. Teams that key from a screen take a spreadsheet, which is what the purchase order PDF to Excel converter produces, or CSV when the ERP has an import routine that expects it. Teams with a developer or an integration platform take JSON from the purchase order API and write the order themselves. The general shape of that hand off, including the field mapping most people get wrong on the first pass, is set out in how to import purchase orders to your ERP, and there are documented routes for NetSuite, SAP, Acumatica, and Epicor.
It is worth separating two things that get sold together. Capture is reading the document. Automation is everything after: validating the customer and part numbers against ERP reference data, applying contract pricing, creating the order record, handling exceptions, and acknowledging back to the customer. The platforms compared below do both. This tool does the first one well and hands you the result. If the workflow half is what you are missing, sales order entry automation covers how that end to end process is usually built, and the sales order entry process walks the steps in order.
Two more things worth knowing before you shortlist. First, a large share of B2B order volume never arrives as a PDF at all: it comes over EDI as an EDI 850 purchase order, and OCR has nothing to do with those. If most of your volume is EDI and the PDFs are the tail, solve the tail cheaply and leave the EDI pipeline alone. Second, if you are clearing a backlog rather than handling today's mail, bulk purchase order upload processes a stack in one batch instead of one file at a time.
Conexiom and Esker are the established names in sales order automation and both do more than this tool does. The honest comparison is scope against speed to start. Figures come from each vendor's own product pages, verified September 2026.
| PurchaseOrders | Conexiom | Esker | |
|---|---|---|---|
| What it is | Document capture only | Order and invoice automation platform | Order to cash automation suite |
| Reads unseen layouts | Yes, no template per customer | Yes, stated across many formats | Yes, deep learning on first sighting |
| Writes the order into your ERP | No, you or your code do | Yes, 40+ ERPs named | Yes, validates against ERP reference data |
| Validates against customer and part master | No | Yes, corrects common order issues | Yes, at header and line level |
| Exception and approval workflow | No | Yes | Yes |
| Published pricing | $49 per month, Starter | Not published, quote only | Not published, quote only |
| Free access without a sales call | 25 pages, no card, no expiry | No, demo request | No, demo request |
| Stated time to live | Same day, self serve | 30 day average implementation | Implementation project, timeline quoted |
| Vendor published results | None claimed | 56% no touch orders, 89% of common order issues corrected | 74% of orders fully automated at one named customer |
| Output you can take away | Excel, CSV, Google Sheets, JSON | Data written to the ERP | Data written to the ERP |
| Best for | Capturing PDF orders without a project | Distributors standardizing high order volume | Enterprises automating the whole order to cash cycle |
Conexiom figures are taken from the sales order automation page on conexiom.com, verified 9 September 2026: a 30 day average implementation with zero ERP changes required, 56% no touch orders, 89% of common order issues corrected automatically, and more than 40 named ERP integrations including SAP, Infor, Epicor, Oracle NetSuite, Microsoft Dynamics 365, Acumatica, Sage, IFS and Syspro. Esker figures are taken from the order data capture page on esker.com, verified 9 September 2026, which describes Esker Synergy AI as deep learning recognition, machine learning from user corrections, and manual teaching for recurring orders, and cites 74% of orders fully automated with no changes at Heineken. Neither vendor publishes list pricing; confirm current terms and figures with each vendor directly.
Accuracy claims mean nothing until they are run against the layouts your customers actually send. This takes a few minutes and no contract.
Take a real PO out of the order inbox as a PDF, a scanned fax, or a photo. No field schema to define and no template to build first.
Tip: Use your worst layout, not your cleanest one. The messy account is the one that decides this.
Confirm buyer, ship-to, PO number, requested date, and terms, then check the item grid line by line for part number, quantity, unit of measure, and price.
Tip: Unit of measure is the field most worth checking. It is the one that causes wrong shipments.
Download Excel, CSV, or Google Sheets for a person to key from, or take JSON from the API and let your integration create the order.
Sales order OCR is software that reads an incoming customer purchase order and converts it into structured data your systems can use. It captures header fields such as buyer, ship-to, PO number, requested date and terms, plus every line item with part number, quantity, unit of measure and price, and returns them as a spreadsheet or JSON instead of a PDF someone retypes.
The document is converted to text, either directly from a native PDF or through an OCR engine for scans and photos. A model then identifies which values belong to which fields and reconstructs the line item grid as rows. Modern tools use machine learning rather than fixed coordinates, so a layout the system has never seen still parses without a template.
OCR is capture: turning the document into data. Automation is everything after it, including validating the customer and part numbers against your ERP, applying contract pricing, creating the order record, routing exceptions and sending an acknowledgment. Capture tools stop at the data. Platforms like Conexiom and Esker do both, which is why they are implementations rather than sign ups.
Neither Conexiom nor Esker publishes list pricing, so both require a quote scoped to your order volume, ERP and document mix. Capture-only tools are priced openly by volume: this one starts at $49 a month for 2,500 pages, with 25 pages free and no credit card. If you need a budget figure before a sales call, that difference matters.
Printed and typed orders read reliably. Handwritten values are far less consistent, and a handwritten quantity or part number should always be reviewed by a person before the order ships. If a meaningful share of your volume is handwritten, test that subset specifically rather than assuming the overall accuracy figure applies to it.
Not with a machine learning based reader. Template or zonal systems map field positions per layout, which works until the customer changes their form, and the maintenance grows with every new account. A model trained across many layouts reads an unseen format on the first try, which is what makes a varied customer base workable.
This tool does not. It returns Excel, CSV, Google Sheets or JSON, and your team keys the order or your integration creates it through the API. Conexiom and Esker do write directly into the ERP, Conexiom naming more than 40 supported systems, which is a real advantage of a full platform and the main reason to buy one.
Do not take a general figure on faith. Header fields are consistently easier than line item grids, and your accuracy depends on your customers' layouts, not on an average. Run 20 to 30 real orders covering your messiest accounts, then count field level errors. That number is the only one worth planning around.
No, and it should not. If a customer already sends an EDI 850, that path is structured, cheaper and more reliable than reading a PDF. OCR is for the accounts that will not or cannot trade EDI, which in most distributors is a long tail of smaller customers sending email attachments.
Automate customer PO entry end to end.
The same engine on the buy side.
How the item grid is captured.
Get the order back as JSON.
Turn an order PDF into a spreadsheet.
Clear an order backlog in one batch.
Compare PurchaseOrders with Conexiom.
Compare PurchaseOrders with Esker.
