Managing Requirement Chaos & Variant Complexity With Digital Product Twins

Why a fast quotation process is more important than ever

Machinery manufacturers and Tier-1 suppliers are drowning in individual, unstructured RFQs.

Each request arrives as a bespoke mix of customer specs – usually buried in PDFs, spreadsheets, or long email threads. Sales teams scramble to piece together a quote. Engineering scrambles to check feasibility. Meanwhile, deadlines are missed, and business is lost.

As mechatronic products become more complex, customizable and software-defined, quoting speed is becoming a competitive differentiator. But most companies are stuck manually comparing new requirements with an incomplete picture of what they’ve already built in the past and their existing portfolio. There's no single source of truth.

The cost of a slow quotation process

Quote delays translate not only into lost revenue but also into structural risk.

Every week an RFQ goes unanswered is a potential program handed to a faster competitor. Engineering talent is trapped in quote alignment, blocked from real innovations. And when you build from scratch each time, development costs explode and time-to-market slows down.

How industrial leaders are responding

Leading OEMs and suppliers are rethinking how they quote and develop. Rather than relying on fragmented systems and isolated teams, they’re adopting Agentic Engineering Intelligence.

At the core of our solution are the Product Twins – live, interactive representations of products and their architectures. But how are they built and utilized?

• Rapid Ingestion: SPREAD automatically integrates and contextualizes requirements, quote and portfolio data from PLM, CAD, Excel, PDF, E/E architectures, and more – structured and unstructured – across mechanics, electronics, and software.
• Product Twin: That data becomes a contextualized model of the different products, components, requirements and more  – searchable across variants and visualized in 2D/3D.
• Action Cloud: On top of the twins, SPREAD deploys intelligent pre-configured applications that power cross-functional workflows and collaboration – RFQ management, architecture management, and more. Beyond that, customers can easily build their own applications in a low-code environment.

This is not another siloed tool. It’s a layer of intelligence that makes existing data, systems, and processes smarter – without needing to replace them.

Proven at scale in the automotive sector – where leading OEMs like Volkswagen, Mercedes-Benz and BMW use our platform to manage development complexity, secure SOP timelines, and reduce costs – SPREAD is now bringing its Agentic Engineering Intelligence to improve the quotation process at OEMs and suppliers.

How does it work in practice

Today, teams manually convert heterogenous customer requirements into a structured list of requirements for further processing. The requirements are then validated and compared manually against previous quotes and existing products by Sales and Engineering teams. They are then translated into internal system requirements, as the basis to create the customer quote. This process takes too long and requires extensive alignment between Sales and Engineering.

With SPREAD, incoming RFQs are automatically transformed, analyzed and matched against

components, architectures, and past quotes. The customer requirements are then translated automatically into system requirements, enabling a faster and more accurate quote creation.

The result: Quotation becomes fast, modular, and manageable. Sales can respond in days, not weeks. Engineering avoids lengthy validation and subsequent greenfield designs. Alignment need is significantly reduced.

See it in action

SPREAD already helps machinery OEMs and Tier-1 suppliers like yours quote 3x faster, grow their revenue, and control variant complexity.

Want to see what a data-driven RFQ process looks like in action? Talk to an Expert at SPREAD.