Manufacturers keep their best knowledge on the shop floor and in the estimator's head.
Elevare builds the intelligence layer your business is missing: your documents, systems, customer history, and the knowledge that only lives in people, connected so your team and any AI work from the same picture. In a job shop or contract manufacturer, that knowledge is split between the ERP, the estimator's own pricing sheet, the drawing revisions in a folder tree, and whatever the owner and one salesperson remember about the account.
Where the knowledge lives in a manufacturing company.
Engineering keeps drawings and revisions in a folder tree that makes sense to the people who built it and to nobody else. The customer relationship — who called last, what "rush" actually means to this account, which contact signs the PO — lives in the owner's inbox and one salesperson's memory. Quality history, first-article results, scrap and rework, sits in a binder or a system nobody else opens.
Ask a straightforward question — what did we quote this customer last time, and why did we lose it — and the honest answer is that no single system can tell you. Four or five can each tell you part of it.
What the intelligence layer connects here.
Two things get built first here, on top of what the ERP and the shop already run on.
Growth and Sales Intelligence. The RFQ pipeline and the account history, working together instead of living apart.
- RFQ triage: every inbound request for quote arrives sorted against what the shop already builds well.
- Quote history connected to the part family, so a repeat RFQ pulls its own precedent instead of starting cold.
- Account intelligence for repeat and reactivation: which customers used to order and stopped, and what they used to buy.
- PO history and blanket orders visible next to the quote, not buried inside the ERP.
Company Intelligence. The estimating knowledge, drawing revisions, and quality history connected to the job, not scattered across the building.
- The estimator's pricing logic captured and connected to the quotes it produces, not locked in one spreadsheet.
- Drawing revisions and customer-supplied drawings tied to the right job and the right traveler, version by version.
- First-article results, scrap and rework history, and quality records connected to the customer and the part.
- Capacity and backlog visible against tooling and lead time, so a delivery promise is a real one.
Then Workflows and AI Agents — agents are AI that does one specific job inside a real process — take over the repeatable parts: RFQ intake, a first draft of the quote built from history, and a spec review before the job hits the floor.
Where manufacturers usually start.
Which constraints show up most.
- Revenue. Quotes go out, and the follow-up depends on whoever remembers to do it.
- Intelligence. Nobody can see win rate by part family or by customer, so pricing decisions run on instinct.
- Operations. Capacity and backlog live in someone's head, not in a place the whole shop can see.
What this is not.
- Not a new ERP. We connect what you have.
- Not an MRP replacement or a scheduling rebuild.
- Not a chatbot answering customer questions on the website.
Written for manufacturers.
What manufacturers ask.
Do we have to replace our ERP?
We run on spreadsheets for estimating; is that a problem?
Can this work with customer drawings and specs?
Where does a job shop usually start?
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