How Product Orchard helped a leading North American memorial plaque manufacturer transform a fragmented, error-prone fulfillment process into a faster, more accurate workflow.
The company served places of worship with specialized memorial plaque and donor recognition products, but its ordering workflow was deeply manual. Customers submitted orders in inconsistent formats, Hebrew names and dates introduced frequent errors, and admins spent days validating and re-entering information into legacy downstream systems. Product Orchard redesigned the workflow end to end — combining guided intake, AI-assisted order extraction, automated purchase order generation, and browser-based automation — to reduce turnaround time from four days to four minutes.
Leading North American memorial plaque manufacturer serving places of worship
Manual, inconsistent ordering workflow with high error rates and legacy fulfillment dependencies
Redesigned intake, validation, formatting, and foundry submission using AI and automation
Reduced average foundry submission time from 4 days to 4 minutes
The company's customers were often place-of-worship employees with deeply established habits and limited comfort with digital tools. Orders came in through whatever channel customers were used to: PDF forms, emails, handwritten notes, and photos of completed forms.
That inconsistency created constant manual cleanup. Admin staff had to review submissions, interpret incomplete information, follow up with customers to correct mistakes, and convert each order into the format required by the foundry.
The workflow was made even more fragile by the need to render Hebrew names and dates correctly. Customers were often expected to encode Hebrew characters into a numeric system — a requirement that introduced confusion, rework, and a high cost of error. Roughly 30% of orders required correction before they could move forward.
Once the order was finally validated, admins still had to manually populate a purchase order template and re-enter the same information into the foundry's system, including attaching the purchase order as part of the submission process. What should have been a straightforward operational flow often took around four days.
Rather than forcing every customer into a single new way of working, Product Orchard redesigned the system around the real constraints of the business: low-tech users, inconsistent intake channels, specialized Hebrew requirements, customer-specific formatting rules, and a downstream foundry running on legacy systems.
The goal was not to layer AI onto a broken process. It was to reduce friction at each step of the workflow, automate the repetitive parts, and preserve flexibility where customer behavior was unlikely to change.
For customers willing to adopt a better ordering experience, Product Orchard built a guided input form that structured submissions at the source. The form reduced ambiguity and made it easier for customers to provide complete, usable order details without admin intervention.
The form automatically calculated Hebrew dates from English dates and used AI-based transliteration to generate the five most likely Hebrew spellings for a given English name. An on-page Hebrew keyboard was also added so customers could type directly when needed. This removed one of the most confusing parts of the process: manually encoding Hebrew into numeric values.
Not every customer adopted the new form. To support those who still submitted orders through email, photos, and legacy PDFs, Product Orchard built an internal AI-enabled tool for admins. Forwarded materials could be parsed into structured order details, reducing the amount of manual extraction and re-entry required before review.
Validated orders were automatically transformed into the required purchase order format using customer-specific configuration logic. From there, a Chrome extension automated form entry on the foundry's website — a deliberate systems decision. The foundry's stack was too legacy-bound for direct integration, so browser-based automation created a practical path to modernization without waiting on vendor changes or technical cooperation.
The new system is live today. Customers particularly value no longer needing to manually encode Hebrew into numeric values, while admins are ecstatic about the reduction in repetitive work, follow-up, and re-entry across the order process.
The success of the engagement did not come from adding AI everywhere. It came from identifying where the workflow was brittle, where humans were doing low-leverage reconciliation work, and where legacy constraints were blocking progress.
Product Orchard introduced the right mix of guided input, AI-assisted interpretation, customer-specific business logic, and browser-based automation across the actual operating system of the business. The result was a workflow that became faster and more accurate without requiring every customer or vendor in the ecosystem to modernize first.
Mapped the full order-to-foundry process, identified friction points, and defined the highest-value opportunities for automation.
Built and deployed guided intake, AI-assisted order extraction, transliteration support, formatting logic, and browser-based fulfillment automation.
Refined workflows based on live usage, supported rollout, and expanded the system to handle a broader range of customer behaviors and order formats.
If your team is layering AI onto existing processes and wondering why the returns feel marginal, the issue may not be the tools. It may be the workflow. Product Orchard helps organizations redesign how work actually gets done — and embed AI where it creates real leverage.