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Reference Implementation

Manufacturing
RFQ Workflow

An example workflow showing how AI can help manufacturing teams process RFQs, extract requirements, identify missing information, and prepare review-ready summaries.

Explore workflow
RFQ preparation flowDemo data only
  1. 01RFQ email + technical document
  2. 02AI requirement extraction
  3. 03Engineering review
  4. 04Quote preparation

What this demonstrates

AI structures the RFQ. Engineering retains the commercial decision.

Requirements made visible

Extract product, quantity, material, and specification details into a consistent review packet.

Missing information surfaced

Make tolerances, certifications, and other quote-critical gaps visible before a commitment is prepared.

Review-ready preparation

Give engineering and commercial owners a clear starting point without granting the system authority to quote.

Interactive sandbox

Turn a sample RFQ into a review-ready quote brief.

Demo data only. Files remain in this browser and are not uploaded, parsed, or sent to external systems.

Manufacturing RFQ copilotSample data / no external connections
1. Upload RFQ email or document
RFQ analysis flowReady
  1. 01
    RFQ received

    Waiting for upstream step

    waiting
  2. 02
    Requirement extraction

    Waiting for upstream step

    waiting
  3. 03
    Quote preparation

    Waiting for upstream step

    waiting

Analyze the sample request to see the requirements, missing information, and review points prepared for a quote workflow.