AI Interpreter

AI Interpreter is a document-processing tool that reads incoming business documents — purchase orders, invoices, quotes, packing slips, and advance ship notices — and converts them into ERP-ready orders automatically. Instead of someone manually retyping information from a PDF or email attachment into your ERP, AI Interpreter extracts the header details and line-item data directly from the document itself. It identifies key fields like item numbers, quantities, pricing, and shipping information, then structures that information into the format your ERP expects. If something is missing, unclear, or doesn't match existing records, AI Interpreter flags it as an exception so a person can review and resolve it before the order is finalized, rather than letting incomplete or incorrect data flow straight through. The result is a much faster path from "document received" to "order created," with far less manual re-entry and fewer opportunities for typing errors to creep into your ERP data.

AI Interpreter is built to handle the common documents that drive order creation in manufacturing and distribution environments, including purchase orders, invoices, quotes, packing slips, and advance ship notices. These documents can arrive as PDFs, scanned images, or email attachments, and AI Interpreter reads the unstructured content in each one to identify the fields that matter — item numbers, descriptions, quantities, unit pricing, ship-to information, and requested dates, among others. Because incoming documents rarely follow one consistent template, especially when they're coming from many different customers or suppliers, AI Interpreter is designed to adapt to varying formats rather than requiring every document to match a fixed layout. If your team regularly processes other document types beyond these and wants to know whether they're supported, that's worth raising directly, since coverage continues to expand based on what customers actually need to automate.

Agility Intelligence's AI tools, including AI Interpreter, are built around a 98%+ accuracy standard for the data they extract and process. In practice, that means the vast majority of fields pulled from an incoming document — item numbers, quantities, pricing, dates, and similar details — are captured correctly without any manual correction needed. For the small percentage of cases where a field is missing, ambiguous, or doesn't match what's expected in your ERP, AI Interpreter flags the issue as an exception rather than guessing or letting bad data flow through silently. That exception gets routed for human review before the order is finalized, which is an important safeguard: it means the accuracy figure reflects real-world performance with a review step built in, not a claim that every document is processed with zero oversight. Over time, this combination of high extraction accuracy and built-in exception handling is what keeps error rates low without requiring a person to re-check every single order.

When AI Interpreter encounters a document with missing fields, unclear handwriting, or details that don't match existing records in your ERP, it doesn't guess or push incomplete data through automatically. Instead, it flags the specific field or line item as an exception and surfaces it for a person to review. That gives your team visibility into exactly what needs attention — rather than having to re-check an entire document from scratch — and lets them resolve the issue before the order is created in your ERP. This exception-handling step is a deliberate part of the design, not a limitation: it's what allows AI Interpreter to run with a high degree of automation while still keeping a human in the loop for the cases that genuinely need judgment. As your team resolves exceptions over time, patterns in what's commonly missing or unclear can also help inform whether a supplier or document source needs a process change on their end.

AI Interpreter is built to connect directly to SAP Business One and Macola using each platform's native APIs and service layers, so most customers don't need custom middleware or a separate integration project to get started. Because the tool writes finished orders directly into the ERP you already use, there's no intermediate database to maintain and no need to keep a second system synchronized with your ERP over time. That said, every environment is a little different — document formats, approval workflows, and field mappings can vary by customer — so implementation typically includes a discovery step to confirm how documents should map into your specific ERP setup before going live. This is generally a configuration exercise rather than custom software development, and most customers are able to move from initial setup to a working pilot fairly quickly, especially when starting with a single document type before expanding to others.

Not exactly. Traditional OCR (optical character recognition) is primarily about converting an image or scanned document into readable text — it tells you what characters appear on a page, but it doesn't inherently understand what that text means in the context of your business. AI Interpreter goes a step further: after extracting text from a document, it identifies which parts represent specific, meaningful fields — item numbers, quantities, pricing, ship-to details — and maps that information into the structure your ERP requires to create a valid order. It also applies judgment that basic OCR can't, such as recognizing when a field is missing or doesn't match expected values and flagging it as an exception rather than passing through incorrect data. In short, OCR is one part of the process, but AI Interpreter's value comes from the interpretation and structuring layer built on top of it, which is what turns raw extracted text into a usable, ERP-ready order.