Zero RFQ is a sourcing approach in which AI predicts the price of a newly designed part from its drawing, 3D model and purchasing history, then proposes a matching incumbent supplier, so no request for quotation is sent. According to PartSpace’s field report from the 15th BME Value Day at ZEISS in Oberkochen, AI can source over 60% of newly designed parts this way, directly from existing suppliers. Procurement shifts from processing quotes to validating prices. RFQs remain for novel, complex, strategic or critical parts.

Key takeaways

• Over 60% of newly designed parts can be sourced from incumbent suppliers with zero RFQ (PartSpace field report, October 2026).

• Siemens Mobility identified a 7–12% annual savings potential across its entire build-to-print portfolio.

• Horsch identified and implemented a 12% savings potential across 10,000+ parts, with ROI in a few weeks.

• BHS Corrugated already sees around 20% process improvement and expects 50–60% time savings with an ERP interface.

• Zero RFQ does not replace procurement: the AI reports its own confidence, and uncertain prices go to review.

Why is the RFQ the costliest step in procurement?

“The costliest step in procurement is the one nobody counts,” said Steffen Loose of PartSpace at the BME Value Day. In almost every machinery and plant engineering company, every newly designed part triggers the full RFQ process: drawing, RFQ, collecting quotes, bid comparison, award. That happens regardless of the part’s value or risk.

This path has three structural problems:

• It’s manual. It is rarely digitalised end to end.

• Price knowledge arrives too late. It comes only after quote rounds, long after design decisions are fixed.

• It doesn’t scale. Classic bid comparison grows linearly with the number of new parts.

Digitalising the RFQ makes this process faster. As the report puts it, it doesn’t make it unnecessary.

What is Zero RFQ?

Zero RFQ starts from one premise: “The best RFQ is the one you never have to send.” Most sourcing decisions for recurring part types don’t need a market test. They need a reliable price. In Loose’s words: “Not every sourcing decision needs a market. Most only need a reliable price.”

When drawing, 3D model, bill of materials and purchasing history come together on a technical level, the price of a new part can be predicted before a single supplier is asked. That also gives you cost transparency in the design phase, while changes are still cheap.

How does AI predict the price of a new part without an RFQ?

The AI reads the technical drawings (2D and 3D STEP), bills of materials and purchasing history already sitting in your CAD, PLM and ERP systems. technik-einkauf From these it produces:

• A should-cost analysis per part, broken into traceable cost blocks such as material, machining and finishing. partspace There is no black-box price.

• Similarity analysis and clustering, which find comparable and duplicate parts you have bought before. partspace

• Benchmarking and outlier detection, which flag prices that don’t match their cost drivers. technik-einkauf

• A supplier recommendation: the incumbent best suited to the part. vogel

Buyers validate the proposed price and decide. Every decision feeds back into the models, so the system keeps learning.

In the full report you’ll find a worked cost-breakdown example for a real part, showing how each cost block adds up to the AI price and what it reveals about cost drivers.

Which parts qualify for Zero RFQ and which don’t?

Zero RFQ is not a blanket rule. The report sets clear limits:

The boundary comes from a model output, not gut feeling: the AI reports its own confidence for every price.

What results have manufacturers achieved?

Results vary by portfolio and data quality, but three customers in the report show the range:

• BHS Corrugated buys around 10,000 build-to-print parts a year, with about €40 million in annual purchasing volume in the category. simplify It is replacing manual RFQs step by step and realised six-figure savings in 2025. “Right now we are seeing a process improvement of around 20%. With the planned interface and a more seamless data exchange, we expect 50 to 60% time savings,” says Johannes Rupprecht, Head of Purchasing, BHS Corrugated & GKS. partspace

• Siemens Mobility combines procurement, production, engineering and re-use views on one data model, with no manual data entry. The result is a 7–12% annual savings potential across its entire build-to-print portfolio. Berthold Weiss (Siemens Mobility) and Steffen Loose presented the approach at the 25th VDI-Tagung Wertanalyse 2026 in Wuppertal.

• Horsch analysed 10,000+ parts with a core team of two. It identified and implemented a 12% savings potential, and reached ROI within a few weeks. partspace The AI-predicted prices and flagged outliers went straight into supplier negotiations.

In the full report you’ll find the complete BHS Corrugated case: the four-stage roadmap from price validation to Zero RFQ, and why each stage carries its own business case.

How do you get started with Zero RFQ?

You don’t need a big-bang project. The report recommends a pilot on a single part family, with no ERP integration and no up-front data cleansing. A typical PartSpace roll-out takes six weeks to go-live. partspace

In the full report you’ll find the five-step guide to getting started, from baseline data and governance to quick wins and embedding the approach in daily work.

What’s inside the full report?

The free PDF field report “Zero RFQ: Best price without a single RFQ” includes:

• The full argument from the BME Value Day talk at ZEISS

• How the AI gets from drawing to price, step by step

• A worked should-cost breakdown for a real part

• The complete BHS Corrugated case and its four-stage roadmap

• The Siemens Mobility and Horsch proof points in detail

• A five-step guide to your first Zero RFQ pilot

→ Download the full guide: “Zero RFQ: Best price without a single RFQ”