What is the difference between quoting software and should-cost software?

Quoting software helps a manufacturer produce its own quote in response to an RFQ. Should-cost software, aPriori, Costimator, helps an OEM or buyer estimate what a part ought to cost to manufacture, typically from the 3D CAD model, for design-to-cost decisions and supplier negotiation. They sit on opposite sides of the same negotiation, and it is common for a supplier quoting with its own tools to face a buyer armed with should-cost benchmarks.

Do I need to replace my CPQ or ERP to automate quoting?

Usually not. If you run Salesforce CPQ or a shop ERP, the slow step is rarely your pricing rules, it is getting complete, structured requirements out of drawings, spec sheets, and email threads into the system. Mavlon reads the whole package and produces a priced draft quote in your own pricing, and the same structured lines can go into your existing CPQ or ERP, which fixes the bottleneck without replatforming.

The 2026 Buyer Guide

Manufacturing quoting software, compared honestly.

Q: What is the best quoting software for a custom manufacturer?

It depends on what your RFQs look like and where your pricing logic lives. If RFQs arrive as unstructured packages, 2D PDF drawings, scans, spec documents, email threads, and your shop already knows how it prices, Mavlon's AI Quoting Engine turns the package into a priced draft quote in your own pricing within minutes, and your estimator sets the final number. If your work arrives as clean CAD files, Paperless Parts builds geometry-driven quoting workflows for job shops. If you need should-cost benchmarks from 3D models, aPriori and Costimator are the simulation lane. If you run a shop ERP like JobBOSS2 or MRPeasy, its quoting module keeps everything in one system at the cost of manual data entry.

Q: Does AI quoting software invent the price?

The serious answer is that it should not. A shop's pricing logic, rates, margins, history with similar parts, risk rules, is the asset that wins work. Mavlon deliberately carries no cost models: it reads what the bid package asks for and applies the shop's existing pricing, so the number produced is the shop's own number, faster. Simulation tools like aPriori work the opposite way by design: they compute a should-cost from their own physics-based models, which answers a different question, what a part should cost, not what your shop will quote.

Nine serious tools, four different lanes. Most comparison pages pretend they compete. They mostly answer different questions.

By Atishay Jain, founder of Mavlon · Updated October 2026

Quoting and estimating software helps a manufacturer turn an RFQ into a priced quote. The tools split into four lanes that are routinely confused: should-cost simulators that compute what a part ought to cost from 3D CAD, geometry-driven quoting platforms that price from CAD files, ERP and CPQ modules that price from structured records someone must first fill, and AI quoting that turns the customer's whole bid package into a priced draft quote in the shop's own pricing. Picking the wrong lane is the most common quoting-software mistake.

This guide compares Mavlon, aPriori, Costimator, Paperless Parts, SecturaFab, Tempus Tools, ECI JobBOSS², MRPeasy and Salesforce CPQ. Mavlon is our product, so read the table with that in mind. Every claim about the other tools comes from what they publicly document, and where they are strong we say so.

The short answer

Which quoting software should you pick?

Your requests arrive as bid packages: a specification, drawings (often scans), a bid form and email threads, and you price by your own logic

Mavlon. Its AI Quoting Engine turns the whole bid package into a priced draft quote in your own pricing within minutes. Every line carries the page that asks for it, and where the documents disagree the draft prices both readings. Your estimator checks the draft and sets the final number. No 3D model is needed, and there are no cost models to maintain.

You are an OEM doing design-to-cost or negotiating supplier pricing with should-cost benchmarks

aPriori. The established should-cost platform: simulates manufacturing from the 3D CAD model in configured digital factories with its own library of process and cost models.

You want feature-based cost estimates with a maintained cost-model database

Costimator. MTI Systems' long-standing estimating tool with process-based cost models for machining and fabrication.

Your machine shop receives CAD files and wants a geometry-driven quoting workflow

Paperless Parts. Analyzes uploaded part geometry, applies your configured shop rates, and wraps quoting in a modern collaboration workflow built for job shops.

You cut sheet and plate and price nested laser, plasma, or waterjet parts

SecturaFab or Tempus Tools. Fabrication-lane quoting: cut-time and nesting-aware pricing for flat parts, with Tempus focused on laser job shops.

You already run a job-shop or small-manufacturer ERP and want quoting inside it

ECI JobBOSS² or MRPeasy (and their ERP peers). Quotes built from estimates and routings in the same system as orders and scheduling; the data entry is on you.

Your company mandates enterprise CPQ

Salesforce CPQ, kept, not replaced. Its rules engine prices well once fed structured data. The fix for slow CPQ quoting is the intake, which is where an AI front end belongs.

If the choice in front of you is your ERP's quoting module or a CPQ, CPQ vs ERP for quoting settles it by what your quote starts from, and it sends most readers to one of the two.

Before the table

What to actually look for in quoting software

Feature lists blur together. These six questions separate the lanes fast:

What does your RFQ actually look like when it arrives?

Be brutally honest here. If it is a clean 3D model, the geometry lane opens. If it is eleven attachments, 2D PDFs, two scans, a spec document, and quantities pasted into an email, then any tool whose first input is CAD geometry starts with a gap your estimator fills by hand. Most custom-manufacturing RFQs are the second kind.

Whose pricing logic produces the number?

Three answers exist: the vendor's cost models (aPriori, Costimator), your configured rates applied to analyzed geometry (Paperless Parts), or your existing logic and quote history applied as-is (Mavlon). None is wrong, but they answer different questions, and a should-cost benchmark is not your quote.

Who maintains the models, rates, and rules?

Simulation platforms need digital factories configured and kept current. Geometry platforms need pricing engines set up per process. Ask who in your team owns that maintenance, and what happens when nobody does. Tools that learn from your existing quotes shift that burden to software.

What happens to the unstructured 80 percent?

Spec PDFs, notes on drawings, requirements buried in email threads, the quantity table in the customer's own format. This is where quoting hours actually go, and most tools in every lane assume someone has already turned it into structured input. Ask each vendor to demo on a real, messy package, not their sample part.

Is feasibility screened before hours are spent?

The most expensive quote is the one you should never have written. Screening an RFQ against your real capabilities on day one, the way Montanstahl ran Mavlon across three plants, stops dead-end quotes before they take an estimator's afternoon.

Does it feed the systems you already run?

If a CPQ or ERP is your system of record, the quoting tool must write clean records into it, not become a second silo. The practical test: where does the structured data land when the quote is done?

Side by side

The comparison table

Tool	Lane	Native input	Pricing logic source	Built for	Best for
Mavlon	AI quoting	The whole bid package as it arrives: specification, drawings and scans, bid form, emails	Your own rates, costing spreadsheets and past quotes; nothing invented	Custom manufacturers answering bid packages	A priced draft quote within minutes, every line tied to its page, open decisions priced both ways
aPriori	Should-cost simulation	3D CAD model plus production inputs	aPriori's process and cost model library in configured digital factories	OEM cost engineering, procurement	Design-to-cost, supplier negotiation benchmarks
Costimator	Cost estimating	Part features, prints, or CAD	MTI's process-based cost models plus your labor and rate data	Estimating departments	Feature-based machining and fab estimates with a maintained model database
Paperless Parts	Geometry quoting platform	Uploaded CAD files, 3D and 2D	Your configured rates applied to analyzed geometry	Machine shops and job shops	CAD-file RFQs, modern quoting workflow and collaboration
SecturaFab	Fabrication quoting	Flat-part geometry, DXF and CAD	Cut-time and material models with your rates	Metal fabricators	Laser, plasma, waterjet part pricing with nesting awareness
Tempus Tools	Fabrication quoting	Drawings and DXF for laser parts	Cut-time models with your rates	Laser job shops	Fast laser-cutting quotes
ECI JobBOSS²	ERP quoting module	Structured estimates entered in the ERP	Your routings, rates, and markups in the ERP	Job shops on the ERP	Quotes living beside orders, scheduling, and job costing
MRPeasy	ERP quoting module	A customer order built from items already in the system	Its cost and lead-time estimate from your bills of materials, routings and stock, plus your margin	Small manufacturers on the ERP	Cost and delivery-date estimates for products already set up in the system
Salesforce CPQ	Enterprise CPQ	Structured product and pricing records	Your configured price rules and approval logic	Sales organizations	Rule-based pricing and quote documents once data is structured

Competitor rows reflect each vendor's public documentation as of mid 2026. If something is out of date, tell us and we will fix it: atishay@mavlon.co.

Read the “native input” column again. Eight of nine tools begin with structured input: a 3D model, a DXF, a filled ERP record, clean CPQ data. But quoting hours are not lost after the data is structured; they are lost getting it structured, reading drawings, reconciling specs against emails, chasing what is missing. That is where Mavlon starts: it takes the package as it arrives and ends at a priced draft quote in your own pricing, ready for your estimator within minutes of the package landing.

Tool by tool

Short, honest reviews

Mavlon

Mavlon makes the AI Quoting Engine for custom manufacturers. It turns the bid package as it actually arrives (the specification, drawings including scans, the bid form, addenda and the email thread) into a priced draft quote in your own pricing within minutes. It learns that pricing from your past bid packages, your quotes and your costing spreadsheets. Every line carries a quantity, a price and the page that asks for it. Where the documents disagree, the draft prices both readings so your estimator can switch between them, a line the package does not settle says TBD instead of a guess, and the open questions come written out for the customer. Your estimator checks the draft and sets the final number.

It is live in production at a US manufacturer of engineered waterfront structures, where the drafts land within about 2 to 3 percent of the company's own price on familiar product lines and about 10 to 15 percent on brand-new jobs with many add-ons (see the case study). You can also check the reading yourself: we ran a public 179-page waterfront bid package through it and published the result on our pilot page, with 214 statements, each cited to its page. An earlier version of the same engine answered feasibility questions at Montanstahl across three plants.

The honest limits: it is not a should-cost simulator, and it carries no cost models of its own by design. It does not create drawings or fill in the customer's forms. It is built for bid packages, so a shop quoting single parts from CAD files is better served by the part quoting tools above. Before it touches a live bid, it is tested blind on jobs you have already priced, against a pass mark agreed in writing.

Our main product page is manufacturing quoting software for custom equipment.

We have a page for each industry we serve: electrical equipment, industrial machinery, process equipment and HVAC equipment.

We also have a page for each kind of product: data center equipment, switchgear, e-houses, battery storage, pressure vessels, heat exchangers, docks and gangways, overhead cranes, fire trucks, water and wastewater equipment and custom metal fabrication.

aPriori

aPriori is the established name in should-cost: per its public materials it breaks a 3D CAD model into geometric cost drivers and simulates manufacturing in configured virtual factories using a large library of process and cost models, returning what the part should cost across processes and regions. OEM cost-engineering and procurement teams use it for design-to-cost and negotiation, and at that job it is genuinely strong. It is an enterprise platform with configuration to own, and it starts from CAD geometry, which is precisely why it is the wrong lane for a job shop whose RFQs arrive as scanned PDFs. See Mavlon vs aPriori for the full side-by-side.

Costimator

Costimator (MTI Systems) has decades in cost estimating: feature-based estimates built on process cost models and time standards, with your shop's labor and overhead rates layered in. Estimating departments that want a maintained model database and repeatable feature-driven estimates use it well. Like all model-driven tools, it prices what is entered into it; reading the customer package and structuring it remains the estimator's job.

Paperless Parts

Paperless Parts is the modern quoting platform for machine shops: upload part files and it analyzes the geometry, applies your configured pricing, and wraps the process in quoting workflow, collaboration, and a clean customer-facing experience. For shops whose RFQs arrive as usable CAD files it is a genuinely strong product with real momentum. Its lane is geometry-driven: the platform prices from part files plus your configured process logic. When the package is scans, spec PDFs, and email requirements, the reading still lands on the estimator, which is the gap Mavlon is built for; some shops run both.

SecturaFab

SecturaFab (SecturaSOFT) quotes fabrication: flat-part pricing from DXF and CAD with cut-time modeling and material awareness for laser, plasma, and waterjet work. Fabricators pricing nested flat parts get fast, consistent numbers. It is process-specific by design; milling-and-turning-heavy or documentation-heavy RFQs sit outside its lane.

Tempus Tools

Tempus Tools' ToolBox focuses on laser job shops: drawing and DXF in, cut-time-based laser quote out, with your rates configured. Shops that live on laser cutting and want quotes out in minutes use it exactly as intended. Like SecturaFab, it is deliberately narrow, one process lane, priced fast.

ECI JobBOSS²

JobBOSS² and its job-shop ERP peers put quoting inside the system that already runs the shop: estimates built from routings and rates become quotes, then orders, then scheduled jobs, one record all the way through. That continuity is the real argument. The cost is manual intake: someone reads the customer package and types the estimate in, and the ERP prices what it is given. ERP shops fix the intake, not the ERP.

MRPeasy

MRPeasy is a cloud manufacturing ERP for small manufacturers. Its public demo shows the quoting flow: you create a customer order with the products and quantities, press “Estimate Costs and Dates”, and it works out the cost, a sales price with your margin, the earliest delivery date and a cost breakdown from your bills of materials, routings and stock. For a small company quoting products it has already set up in the system, that is a quick and honest way to price. It prices what is in the system, so a custom request still has to be read and turned into items, bills of materials and routings by someone before the estimate can run.

Salesforce CPQ

Salesforce CPQ and enterprise CPQ generally are rule engines: given structured products, options, and pricing logic, they price accurately, enforce approvals, and generate quote documents at scale. Manufacturers struggle with them for one reason: an RFQ made of drawings and emails is not structured input, so an estimator becomes the human ETL between the inbox and the CPQ. The answer is rarely replacing the CPQ; it is putting an intake layer that reads the package in front of it.

The table is our opinion. Your RFQ is the proof.

Bring one real package you have already priced. We read it together on a call, and you compare what it finds with what your team found.

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Frequently asked questions

What is the best quoting software for a custom manufacturer?

Match the tool to your requests. Bid packages priced in your own pricing: Mavlon, which turns them into a priced draft quote within minutes. Clean CAD files into a geometry-driven workflow: Paperless Parts. Should-cost benchmarks for design-to-cost: aPriori or Costimator. Fabrication cut-parts: SecturaFab or Tempus. Already on a shop ERP: its quoting module, with the intake fixed in front of it.

Does AI quoting software invent the price?

It should not. Your pricing logic is the asset that wins your work. Mavlon carries no cost models: it reads the bid package and applies your existing rates, rules, and history, so the output is your number, faster. Simulation tools compute their own should-cost by design, which answers a different question.

Quoting software vs should-cost software, what is the difference?

Quoting software helps a manufacturer produce its own quote. Should-cost software helps a buyer estimate what a part ought to cost, from 3D CAD, for negotiation and design decisions. Opposite sides of the same table, and both may be present in one deal.

Do I need to replace my CPQ or ERP?

Usually not. The bottleneck is rarely your pricing rules; it is unstructured intake. And if you run no CPQ at all, Mavlon itself drafts the quote in your own pricing logic. An AI layer that reads drawings, specs, and emails and writes clean records into your existing CPQ or ERP fixes the slow step without replatforming.