Pricing & Quoting

Stop Losing Margin in Manual Pricing

We build custom AI systems for manufacturing quoting that adapt to your real processes, not the documented ones.

Industry Context

Manufacturers face heavy margin pressure from global competition, volatile material costs, and complex compliance requirements. Custom orders with unique specs, tight deadlines, and regulatory constraints (like REACH or DFARS) make manual quoting error-prone and slow. An aging workforce compounds the problem -- tribal knowledge walks out the door, and new hires lack the experience to price accurately. Delayed or wrong quotes mean lost orders or eroded profits.

By the Numbers

margin erosion from inaccurate cost-to-serve models

McKinsey Pricing, 2024

5 days

average time to generate a custom manufacturing quote

Deloitte Manufacturing, 2025

60%

faster quoting with AI-driven configurators

Gartner Manufacturing, 2025

The Problem

What you're dealing with

Engineers manually cross-referencing Excel spreadsheets, supplier catalogs, and ERP data to build a quote -- taking hours per request.

Quotes submitted with outdated material costs or missed compliance markups, leading to costly rework or violations.

Sales quoting inconsistent discount tiers because approval rules live in someone's head, not in a system.

Custom configurator requests stuck in IT backlog for months while opportunities expire.

New hires struggling to price complex assemblies correctly, resulting in either lost deals or negative margins.

The Solution

How it works

We start by mapping your actual quoting process -- not the official version -- through AI-driven interviews with your engineers, sales, and operations teams. We identify where delays, errors, and inconsistencies happen. Then we design a custom AI system that connects to your ERP, CRM, and supplier portals. It pulls real-time material costs, applies your business rules (compliance markups, discount tiers), and generates accurate, compliant quotes in minutes. We build and deploy this on our proprietary platform, which speeds up integration and testing. You get a system that works within your existing tools, with no generic SaaS limitations. The result: quotes that are fast, consistent, and margin-accurate.

Arc

AI-driven process discovery and integration with your existing ERP and CRM systems

POI

Custom logic deployment for pricing rules, compliance checks, and real-time data sync

In Practice

Before and after

Before

A request for a custom enclosure quote arrives. An engineer spends 2 hours manually checking material costs in the ERP, emailing suppliers for lead times, applying compliance markups from a printed guide, and building an Excel quote. Sales reviews it, asks for a revision, and finally sends it -- a day later.

After

The request enters the custom AI system we built. It pulls current material costs automatically, checks compliance requirements, applies business rules, and generates a validated quote in 90 seconds. Sales gets a ready-to-send PDF with all approvals baked in.

1 Request entered via web form or email
2 System validates specs against compliance and internal rules
3 Real-time cost and lead time data pulled from connected systems
4 Quote generated with margin breakdown and approval flags
5 PDF delivered to sales with audit trail

4 weeks

from kickoff to live pilot

For a mid-sized automotive parts manufacturer with custom ERP and 500+ SKUs

FAQ

Common questions

How long does it take to build a custom quoting system?

Typically 4-6 weeks from discovery to deployment. Our internal tooling speeds up integration and testing.

What if our ERP is outdated or custom-built?

We work with legacy and custom systems regularly. Our platform handles API gaps, file-based exchanges, and even manual data entry points.

Who maintains the system after deployment?

We hand over a fully documented system. Your team can update rules and configurations. We offer support plans for complex changes or expansions.

How do you ensure quote accuracy?

We validate the system against historical quotes and run parallel tests before cutover. The AI also flags anomalies for review.

What's the ballpark cost?

Projects range from $150K to $400K depending on complexity. We provide fixed-scope proposals after discovery.