# Automating sales order entry from emailed purchase orders Purchase orders arrive by email as PDFs, spreadsheets and free text, and someone keys every line into the ERP. For one wholesale distributor that became a checked pipeline, then the same approach ran across every country in a group. 10 → 1 About 90 percent less manual work, over 95 percent line accuracy People needed for order entry at a wholesale distributor, client-confirmed. ## The problem Customers send orders the way they like, a PDF from their own system, a spreadsheet, a line of text in an email. Every line has to be matched to the right item, unit and price in the ERP and keyed before the order can be picked. The reading is not the hard part. The hard part is that a customer's description or part number rarely matches your item code, and a wrong match ships the wrong goods. ## How the pipeline works The system treats order entry as a data problem first and an AI problem second. 1. An agent reads each incoming order, whatever the format, and extracts the customer, lines, quantities and dates. 2. Each line is matched to an item in the catalogue, using the customer's own history and cross-references where they exist. 3. Checks confirm the customer, units, pack sizes and prices before anything is written to the ERP. 4. Lines the checks cannot confirm go to a person with the reason, instead of being guessed. Accuracy is measured per line against what the team would have keyed, not per order, because one wrong line in an otherwise perfect order is still a wrong delivery. ## What changed At a wholesale distributor, order entry went from a ten-person task to one, about 90 percent less manual work at over 95 percent line accuracy. In a multi-country distribution group the same approach took order entry from five people to two in each country, about 60 percent less manual work across every country in the group. ## What a project like this needs from you Access to the systems the work already lives in, usually a mailbox and the system of record, with a login the agent can use safely. The rules written down, or a person who knows them and has an afternoon to explain them. A set of real past cases to test against. Replaying last month through a new version before it goes live is what lets a team trust the change. A named owner for the decisions the agent will not make, and a period where it runs alongside the team in shadow mode before it acts on anything. ## Common questions ### Can AI automate sales order entry from email? Yes, for the common cases, with a person on the rest. An agent reads the order in whatever format it arrives, matches each line to your catalogue and writes it to the ERP only after checks on the customer, units and prices pass. Anything the checks cannot confirm goes to a person. ### How accurate is automated order entry? Measure it per line, not per order. In the distributor system described here line accuracy is over 95 percent, and the remaining lines are routed to a person rather than guessed. Accuracy depends mostly on how well customer descriptions and part numbers map to your item codes. ### What is the hardest part of automating order entry? The catalogue mapping. Customers describe items their own way, with their own part numbers, units and pack sizes. Building and maintaining that mapping decides success far more than the reading does. ### Which ERPs can automated order entry work with? Any ERP that can accept orders through an API, an import or a database interface. The systems I integrate with include Microsoft Business Central, MSSQL-based ERPs and spreadsheets used as a system of record. ## Field notes behind this[OperationsAutomating Order Entry Is a Data Problem Before It Is an AI Problem](https://shurco.ai/insights/automating-order-entry-is-a-data-problem-before-it-is-an-ai-problem/)[DocumentsReading a Document With an Agent Is Easy Trusting It Is the Hard Part](https://shurco.ai/insights/reading-a-document-with-an-agent-is-easy-trusting-it-is-the-hard-part/)[ReliabilityEdge Cases Are Where Production Agents Live or Die](https://shurco.ai/insights/edge-cases-are-where-production-agents-live-or-die/) ## Other problems I have solved[ManufacturingAn AI quoting agent for a manufacturer, from days to hoursThe quoting inbox took one to three days per quote. An agent now reads the enquiry and the bill of quantities and prices it against the live catalogue, behind a rules engine that keeps every price explainable.](https://shurco.ai/solutions/ai-quoting-for-manufacturers/)[Field operationsAutomating multi-site field reporting, from days to minutesDaily reporting across many sites took about three days to compile because the data lived in several places. Collector agents now gather it in parallel, a reconciler merges it and a reporter writes the report.](https://shurco.ai/solutions/multi-site-field-reporting-automation/)[Asset managementDecision support for specialist matching at a global asset managerFinding the right specialist match took about three days, in a setting with real accountability. An audit-grade agent now returns ranked, cited recommendations, and a person makes the call.](https://shurco.ai/solutions/specialist-matching-decision-support/)[StaffingAutomating timesheet processing for a weekly payroll runHundreds of emailed timesheets a week, a hard payment deadline and no room for a wrong payslip. This is how the reading, checking and reconciliation moved to a pipeline of agents.](https://shurco.ai/solutions/timesheet-to-payroll-automation/) ## Have the same problem Each system above was built around one client's process. Yours will differ in the details, which is where the work is. [Tell me what your team spends too long on.](https://shurco.ai/#contact) Web version https://shurco.ai/solutions/sales-order-entry-automation/