AI CPQ for manufacturers

AI CPQ for manufacturers

SalesCFG is an AI CPQ built for manufacturers, distributors, and technical sales teams. Buyers describe what they need in plain language, AI reasons from your product rules and catalogue, and every accepted configuration stays valid, priced, and quote-ready.

What AI CPQ means for manufacturers

Traditional configure-price-quote tools assume the buyer already knows which options to pick. For complex industrial products that assumption breaks down. An AI CPQ for manufacturers closes the gap: it turns messy requirements β€” environment, constraints, dimensions, budget β€” into structured configuration data, then prices and documents it so sales can quote accurately.

The useful question is not whether a platform has AI. It is which layer uses AI, which source is authoritative, and what record the journey creates. In SalesCFG, AI assists intake and guidance while a deterministic rules engine owns validity.

How AI works with the rules engine

AI sits in front of the configurator and around it β€” never in place of the rules that guarantee a valid, reproducible product.

Buyers describe the need in plain language

Instead of hunting through option trees, buyers explain environment, constraints, budget, and goals. The AI asks the next useful question instead of dumping a catalogue on them.

AI reasons from your product rules

The agent is grounded in your manuals, compatibility logic, option data, and configurator rules β€” not generic model knowledge β€” so guidance matches what your engineers actually approve.

Every accepted configuration stays valid

AI proposes and interprets; the deterministic rules engine decides. Pricing, compatibility, and engineering constraints remain the source of truth for anything that reaches a quote or production.

Built for engineer-to-order and configure-to-order

SalesCFG models products, options, prices, dependencies, and compatibility rules, then publishes an embedded configurator for your website and portals. It is made for manufacturers whose products are built to order, not picked off a shelf.

  • Engineer-to-order (ETO) products with deep, interdependent options
  • Configure-to-order (CTO) catalogues with compatibility rules
  • Industrial equipment, custom machinery, and technical components
  • Fluid handling, HVAC, and electrical enclosure product families
  • Distributor and dealer channels that need consistent configuration
  • Technical sales teams that quote engineered products every day

From chat to quote

Vague demand becomes a valid, priced configuration.

A buyer describes a cooling system for a humid warehouse with low ceilings. The AI narrows by space, humidity load, and service clearance β€” then the rules engine validates the resulting configuration and hands sales a clean, quote-ready summary.

Low clearanceHigh humidityService accessValid options only

What the SalesCFG AI CPQ layer does

AI-guided configuration

Qualify intent and prepare quote-ready context from the same configuration and document data, 24/7.

Real-time rules-based pricing

Discounts, quantities, markups, and approvals update live from the same rules that validate the build.

Automated proposals and specs

Generate branded PDF quotes, technical specifications, and user manuals from the selected options.

Valid configurations only

Compatibility and engineering constraints prevent invalid combinations from ever reaching a quote.

Quote-ready handoff

Vague demand becomes structured configuration data your sales and engineering teams can act on.

Grounded in your data

Controlled selling: grounded in your catalogue, reviewed by your team, connected to configurator output.

Workflow capabilities

Illustrative capabilities, not measured customer outcomes. Fit depends on your product data, rules, and sales process.

Guided flow

Guide buyers through product choices using configured rules.

Product rules

Apply configured options and compatibility logic.

Structured data

Carry selected product data into quote workflows.

Document output

Use selections in generated quote and technical documents.

AI CPQ for manufacturers: FAQ

What is an AI CPQ for manufacturers?

An AI CPQ for manufacturers combines configure-price-quote automation with AI assistance. Buyers or sellers describe what they need in plain language, AI interprets the request and asks the missing questions, and a deterministic rules engine validates the configuration, resolves pricing, and produces a quote-ready output. The AI accelerates intake and guidance; the rules engine protects validity.

Does AI make the configuration less reliable?

No. In SalesCFG the AI layer sits in front of the rules engine, it does not replace it. The catalogue, compatibility rules, pricing logic, and engineering constraints remain the source of truth, so every configuration that reaches a quote is valid and reproducible.

Can it handle engineer-to-order and complex custom products?

Yes. SalesCFG models product families, option sets, dependencies, and compatibility constraints so engineered-to-order and configure-to-order products can be guided without invalid combinations slipping through to production.

How long does it take to launch an AI CPQ?

Teams can use the visual builder to model a product family, add product data and rules, and embed the configurator on a site or portal. Setup time depends on the catalog and rule complexity; start with a small scope and validate the outputs before expanding.

Does the AI CPQ generate quotes and documents?

Yes. Selected options flow into branded PDF proposals, technical specifications, and user manuals generated from the same product data, removing manual proposal and document assembly.

Which manufacturers is it for?

SalesCFG is built for manufacturers, distributors, and technical sales teams selling complex, configurable B2B products β€” industrial equipment, custom machinery, technical components, and made-to-order products.

Put an AI CPQ in front of your product data

Turn product options, rules, and document templates into a guided configurator and quote workflow. Start with a focused scope and validate the outputs before expanding.

AI CPQ for Manufacturers