Automating quotation-to-order for custom-manufactured parts

Walk through the quotation-to-order flow and see how customer requests, supplier offers, quotations, and ERP orders are handled in one guided process.

The client is a Swiss distributor of custom-manufactured components. It does not manufacture parts itself. Instead, it sources finished components from a supplier network and re-sells them to individual customers with the targeted pricing margin applied. 
Most inquiries are for custom parts based on technical drawings supplied by the customer.

The company needed to process more inquiries and orders with the same team. A strong Swiss franc had reduced their export business, meaning they had to actively replace lost business rather than wait it out. Scaling the commercial process without expanding the team meant changing how they handled quotations and orders. The existing process ran almost entirely through email.

Customer inquiries arrived together with technical drawings in different formats attached to the email. The team read the drawings manually, identified suppliers able to manufacture the component, and hand-wrote individual requests for quotations.

Supplier responses came back as PDFs, Word documents, or plain-text emails. Each offer required someone to read, interpret, copy, and re-enter information that already existed elsewhere before drafting a customer quotation.

Two structural problems made scaling the process harder. No single consolidated view existed by customer or part, so when an individual part was reordered, the team could not quickly see the previous quotation, the price or terms offered, or the supplier used. A few employees also held supplier knowledge, creating an operational dependency around materials, machining processes, and supplier fit.

Lowgile built an automated order management application on the Lowgile platform, covering the end-to-end process from incoming customer inquiry to supplier order.  AI handles the reading and interpretation work, while the team remains in control of supplier selection, quotation review, and final decisions.

How the process works

-       The system monitors a dedicated email inbox for incoming customer quotation requests.

-       AI interprets the attached technical drawings, while business rules identify suitable manufacturers from a list of strategic suppliers.

-       The team confirms which suppliers to approach, and RfQs are sent automatically, with customer names and logos redacted from the attached PDFs.

-       Incoming supplier offers are monitored and interpreted by AI.

-       The system compares offers by quantity tier and prepares a customer quotation with the target margin applied.

-       Once the customer places an order, the system coordinates the creation of both the customer order and the supplier order in the ERP.

What the platform handles

-       Email parsing across PDF, Word, and ZIP attachments, with automatic language detection.

-       AI-generated part descriptions based on manufacturing methods, drawing geometry, and material information derived from technical drawings.

-       Redaction of sensitive customer information before documents are forwarded to suppliers.

-       A supplier selection matrix, pre-populated from master data, showing which suppliers can manufacture which items.

-       Automated reminders for suppliers who have not responded.

-       Price comparison by quantity tier, with target margins automatically applied and editable at any point.

-       Multilingual response templates and exchange rates updated daily.

-       A searchable history of customer requests and supplier orders by material, drawing number, and status.

Quotation preparation moved from a manual, multi-day effort to a guided process that runs in a fraction of the time. Supplier selection and price comparison are now based on structured data rather than individual recall, and every request, offer and order is recorded in one place.

Supplier knowledge that previously sat with two or three employees is now captured in the system and available to the entire team, reducing a dependency that had become an operational risk. 



The result is improved capacity. The same team can process more inquiries and orders, helping the company replace lost export volume without increasing the headcount.