Manufacturing

Your estimator builds quotes in a spreadsheet, manually calculating materials, labor, and markup — each one takes 2–4 hours and looks different every time.

Manufacturing quoting is slow because it requires pulling pricing from multiple sources, calculating custom configurations, and formatting a professional document. A shop quoting 20 jobs per month at 3 hours each spends 60 hours — and loses fast-turnaround opportunities to competitors who quote same-day.

Three ways to solve this

Pick the tier that matches where your team is today. Each includes a clear workflow, the tools involved, and what you can expect.

Starter

3–5 days

1–10 employees, proposals written from scratch or copy-pasted from old ones, no templates.

Workflow

  1. 1Build 2–3 branded proposal templates in Google Docs covering your most common services.
  2. 2Connect your CRM or intake form to Make: when a new opportunity is created, a proposal draft is generated automatically from the right template with client details pre-filled.
  3. 3Add a notification to Slack: 'Proposal draft ready for [Client Name] — review and send.'
  4. 4Team reviews, customizes the key sections (scope, timeline), and sends — total time: 15–20 minutes instead of 3 hours.

Tools

Outcomes

  • Proposals generated in minutes, not hours.
  • Every proposal is branded, accurate, and professional — no copy-paste errors.
  • Team sends proposals the same day the opportunity is created.
  • Win rate improves because you're consistently first to respond.

Growth

1–2 weeks

10–50 employees, multiple services with different proposal formats, proposals bottleneck at senior staff.

Workflow

  1. 1Create a proposal library: templates for every service, with conditional sections that include or exclude based on client needs.
  2. 2Build a Make workflow that pulls deal data from HubSpot (client info, service selected, deal size) and assembles the right proposal from modular sections.
  3. 3Add pricing logic: based on deal size and service mix, the proposal includes the correct pricing table automatically.
  4. 4Track proposal status: sent, viewed, signed — all synced back to HubSpot so reps know when to follow up.

Tools

Outcomes

  • Proposals assembled from modular, pre-approved sections — consistency without rigidity.
  • Pricing calculated automatically based on deal parameters.
  • Senior staff review proposals in 5 minutes instead of writing them from scratch.
  • Proposal-to-close cycle shortened by 40–60%.

Scale

3–6 weeks

50+ employees, high proposal volume, needs AI assistance and approval workflows.

Workflow

  1. 1Build an AI-assisted proposal engine: Claude or Gemini API generates custom scope descriptions, timelines, and executive summaries based on deal context and historical win data.
  2. 2Implement approval workflows: proposals above a certain value require manager sign-off before sending, routed automatically based on deal size and type.
  3. 3Create proposal analytics: track which sections prospects spend time on, which templates have the highest win rates, and where proposals stall in the review process.
  4. 4Deploy a self-serve proposal builder for reps: select service, enter client details, customize AI-generated sections, get manager approval, send — all from one interface.

Tools

Outcomes

  • AI generates first-draft proposals that are 80–90% ready to send.
  • Approval workflows prevent rogue pricing or scope creep.
  • Proposal analytics reveal what's winning and what's losing deals.
  • Reps produce enterprise-quality proposals independently.

This solution for other industries

Same problem, different context. See how proposal generation automation looks in other industries.

More automations for Manufacturing

Other automation solutions we build for teams in manufacturing.

Frequently Asked Questions

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Tell us where proposal generation is costing your manufacturing team time and we'll map out exactly how to fix it.

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