Quotes in one conversation.
How one manufacturer took custom quotes from days to a single conversation with agentic AI, without laying anyone off.
Built to order.
A family-owned maker of custom industrial equipment. One plant, a sales team and a network of distributors, selling products configured to each customer.
Every quote waited on an engineer.
Sales collected the specs, emailed engineering, waited, then priced it by hand from a spreadsheet. Quotes took days. Distributors went with whoever answered first, and the engineers spent their week on quotes instead of products.
No layoffs. No new platform.
Nobody lost their job and nobody bought new software. The team used the tools the company already allowed, and the people who knew the work stayed at the center of it.
Three moves.
1. Learned the rules. Product rules, options, compatibility limits and pricing logic came out of the spreadsheets and the engineers' heads into one set of rules an AI agent could follow.
2. Ran the quote in one conversation. A salesperson describes what the customer needs. The agent asks the follow-up questions an engineer would ask, checks costs and lead times, and drafts the quote.
3. Knew when to stop. Anything outside the rules is flagged and routed to an engineer, with the details already filled in.
One problem. Thirty days.
Week 1. Sit with sales and engineering. Map how a quote really happens.
Week 2. Capture the rules and pricing. Build the first agent.
Week 3. Run live quotes side by side with the old way.
Week 4. Tune it, train the team and hand it over.
Time back.
Speed. Standard quotes go from days to the same conversation.
Engineering hours. Engineers only see the quotes that truly need them, and get their week back for product work.
People. The salespeople who used to wait now close.
Start with one problem.
Quoting was the first app, not the last. Once the team saw it work, the next problems lined up: engineering changes that reach the floor, product data that stays in sync, the know-how of the people about to retire. One problem at a time, each build sized to the work it takes. That is a buildup, not a layoff.
Composite example based on member work. Client details stay confidential.
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