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Viraj Mahalunkar

Manufacturing · RFQ Automation

RFQ Automation

An RFQ moving from 'drawing received' to 'quotation sent' usually passes through several disconnected manual steps — and every one of them is a place for delay or error to creep in. RFQ automation is about connecting those steps, not eliminating the engineering judgment in between them.

Where RFQs actually lose time

A typical manufacturing RFQ moves through intake, engineering review, costing, and quotation — and between each of those stages, someone is usually re-typing data that already existed in the drawing or the previous step. An engineer reads a title block by eye and types it into a tracker. Someone ballooning a drawing writes dimensions onto a separate sheet by hand. Costing rebuilds the same part data a third time to calculate material and tooling cost. The quotation re-enters much of it a fourth time. Each re-entry step is slow and a chance for a transcription error to reach the customer.

What RFQ automation changes

RFQ automation connects these stages so data entered once — a title block field, a ballooned dimension, a costed line item — carries forward automatically to the next stage, with a confidence-scored review step so engineers verify what the system extracted rather than blindly trusting it. The goal is removing re-typing, not removing engineering oversight.

A real, working example

InFaktory implements this as a seven-step AutoQuote wizard for die-casting RFQs: casting info, machining details, process flow confirmation, costing, quotation, tooling and gauge capture, and export — sitting inside a wider platform that tracks every RFQ through a pipeline and builds a customer CRM automatically as quotes go out. It’s a concrete, currently operating example of this pattern, not a conceptual pitch.

What stays manual, deliberately

Manufacturability judgment, process route decisions, and final commercial sign-off on a quotation stay with your engineers and management — RFQ automation here is explicitly about removing repetitive data work around those decisions, not replacing the decisions themselves. See AI Tools for Manufacturing for more on why that distinction matters.

Starting point for your business

RFQ automation doesn’t have to start as a full platform rebuild — it can start at whichever stage currently causes the most delay or error in your specific process, whether that’s drawing intake, ballooning, or costing roll-up. Get in touch to talk through where that starting point would be for your workflow.

Common Questions

What does 'RFQ automation' actually automate?

The data movement between stages — reading a drawing's title block automatically instead of manual re-typing, carrying extracted data into costing instead of rebuilding it, and carrying costed data into a quotation instead of a third re-entry. The engineering review and approval decisions stay with your team.

How long does a typical RFQ take without automation, versus with it?

It varies hugely by business and part complexity, which is why a general RFQ platform isn't the goal — a system built around your specific drawings and workflow is. InFaktory, the platform this is built around, is specifically aimed at cutting the manual re-entry that stretches a die-casting RFQ out over days; the exact reduction depends on part complexity and how many re-entry steps your current process has.

Does RFQ automation require replacing our entire quoting process?

No — it typically starts at the point of greatest manual pain (often drawing intake and ballooning, or costing roll-up) and extends from there, rather than requiring a full process replacement on day one.

Is this only relevant for die-casting?

The concrete working example (InFaktory) is built for die-casting specifically, but the same pattern — structured drawing intake, engineering review, automated costing roll-up, quotation generation — applies to other manufacturing processes with their own drawing and costing conventions.

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