Intelligent Quoting

Stop losing jobs to bad estimates.

The average job shop loses 15–20% of winnable work to slow turnaround and inaccurate pricing. We build AI quoting systems that turn your historical job data into a competitive weapon — so you respond faster and price with confidence. American shops have the capability; they just need the tools to match.

Intelligent quoting blueprint — AI analyzing cost data and quote workflows
The Problem

Your quoting process is costing you work.

Most shops know they lose jobs to slow quotes. Few realize how much margin they leave on the table with every estimate.

  • 01
    Slow turnaround loses winnable jobs
    3–5 day average quote turnaround is the norm. Shops that respond in hours win 60% more work — but getting there means rethinking the entire intake-to-quote pipeline, not just working faster.
  • 02
    Tribal knowledge lives in one estimator's head
    Your best estimator knows what a part should cost because they've seen a thousand like it. When they're out sick, on vacation, or retire — that intuition walks out the door and your quote accuracy drops overnight.
  • 03
    No quote-vs-actual feedback loop
    You quote a job, run it, and move on. Without systematically comparing estimated costs to actual costs, the same pricing mistakes repeat — and you never know if you're consistently too high (losing work) or too low (losing money).
Outcomes

What changes when quoting gets intelligent.

We don't just speed up your current process — we rebuild estimation around your data so it gets smarter with every job.

Before
RFQs sit in an inbox for days. Estimators manually pull up old jobs from memory or spreadsheets.
After
RFQ to quote in hours. AI parses incoming requests and surfaces the most similar jobs you've already run — with real costs attached.
Before
Quotes are gut-feel estimates. Accuracy depends on who's doing the quoting and what they remember.
After
Every quote backed by historical cost data. Material, labor, setup, and overhead broken down with confidence scores — not guesses.
Before
No visibility into whether you're quoting too high or too low. Margins are a mystery until the job ships.
After
Continuous accuracy improvement. Every completed job feeds back into your cost model — win/loss tracking and quote-vs-actual analysis compound over time.
How We Work

From your data to
a smarter quote.

A focused engagement that connects your job history to an AI-powered estimation engine.

01
Discovery
We audit your current quoting workflow — tools, data sources, pain points. Map your job history and identify the highest-impact integration points.
02
Data Integration
Connect your ERP, job tracking, and cost data. Build the embedding index over your historical jobs so the AI has real numbers to work from.
03
Build & Configure
Stand up the quoting engine — RFQ parsing, similar job matching, cost estimation, approval workflows. Configured to your materials, processes, and margin targets.
04
Launch & Optimize
Go live with your team. Monitor quote accuracy, tune the cost model as actuals come in, and expand coverage to additional part families over time.
Powered by the Quoting Module

This service is built on our Quoting & Estimation module — AI-powered RFQ extraction, pgvector similarity search, structured approvals, and PDF generation. Explore the full technical capabilities.

Explore Module →
Restore the edge

Stop guessing.
Start winning.

Every quote you send without data behind it is a quote priced on gut feel. American shops win on precision — let's bring that to your estimates too.

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