Turn a handwritten note into an order ready for approval

We built a platform that processes orders from end to end—from the moment they arrive, in any format, to the final accounting invoice.

• A single multimodal call reads everything that comes in : PDFs, spreadsheets, photos of handwritten notes, and screenshots. Handwriting recognition is handled by the model itself, without the need for a third-party OCR engine.
• It reconstructs the order : it identifies the customer from the content even when the email has been forwarded, matches informal product descriptions to the catalog, interprets relative dates—like "Friday" or "before Easter"—and reorders pages of a form that were scanned out of sequence.
• The customer's history acts as a tie-breaker, never as the source. When multiple products could fit a description like "vanilla," it selects the one the customer usually orders and notes the reason in the line item comment. It never adds a product that wasn't requested.
• Each line item carries a confidence score. A "usual order" becomes a flagged item for the preparer, not an assumption.
• Nothing enters the workflow without human oversight. Every extracted order is reviewed and must be approved; anything that isn't an order is automatically discarded.
• Once validated, the order flows through to workshop preparation, delivery notes, and the invoice, which is pushed as a draft into the accounting system.

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• You no longer enter orders; you simply review them.
• The messiest channels—screenshots, photos, shuffled pages—are no longer manual edge cases.
• Catalog matching and historical analysis eliminate the risk of incorrect products or quantities at the source.
• Invoices are automatically sent as drafts to your accounting system, with no manual data entry required.
• Human oversight is maintained: no order is processed without approval.