Raw materials have an index, standard parts have a catalog, and custom-engineered parts have historically been a black box. For every manufactured part, the pricing logic is embedded in its geometry, material, tolerances, and manufacturing process, yet a reliable target price is almost always missing. This leaves buyers entering negotiations without a factual basis. This webinar demonstrates how to calculate a transparent target price for any custom part and what that means for your negotiations in practice.

Florian Greulich (Head of Procurement at VEMAG Maschinenbau) and Jan Scholich (Product Development at Tacto) demonstrate in this webinar how AI transforms custom parts from unpredictable outliers into items with clear target prices. VEMAG develops and manufactures filling, portioning, forming, and loading systems "Made in Germany," and they share the perspective of a procurement department managing high part variety and small batch sizes.

The limitations of traditional approaches

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Until now, there have essentially been two paths. The first is manual calculation via design or cost engineering: technically sound, but time-consuming and only feasible for individual parts, not for an entire portfolio with thousands of line items. The second path involves rigid cost models and bottom-up calculations from traditional tools, which require filling out forms but fail to account for the broader procurement context. In practice, this leaves most parts to be managed by gut feeling, without a reliable anchor for negotiations.

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How Tacto Intelligence calculates target prices

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Tacto Intelligence calculates the target price in three steps. First, the drawing is analyzed, including features such as material, tolerances, surface finish, and manufacturing process. Next, this information is integrated with the entire procurement context, including volume, batch size, country of origin, suppliers, machine park, similar parts, and current market trends. In the third step, a target price is generated for every individual part. Crucially, the underlying assumptions are transparent and can be refined by the buyer. This avoids a black-box result, providing instead a traceable price that serves as an anchor for negotiations.

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Beyond the target price

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Once target prices are available for the entire portfolio, the focus shifts from calculating to managing. The AI prioritizes which parts are significantly overpriced, identifies consolidation potential, and uncovers identical parts being purchased at different prices. The webinar showcased two anonymized examples: one part that was not recognized as a mirror-image variant and was therefore purchased at a 50 percent premium, and two technically near-identical parts where a different material caused the price to more than double. In both cases, the target price makes the difference visible and provides the leverage needed for renegotiation or a new request for quote.

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Conclusion

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The VEMAG case study demonstrates that even a diverse portfolio of custom parts can be managed based on facts once a target price is established for every item. Through AI-supported RFQs and renegotiations, the company realized six-figure savings, earning recognition including the BME Procurement Excellence Award. The key is to view the target price not as the final result, but as the starting point for a negotiation on equal footing.

In this webinar recording, Florian Greulich (Head of Procurement at VEMAG) and Jan Scholich (Product Development at Tacto) show how to turn technical drawings into reliable target prices. They explain why custom parts have been difficult to calculate, where traditional approaches fall short, and how Tacto Intelligence calculates a transparent target price for every part in three steps. Using concrete examples, they illustrate how this led to six-figure savings for VEMAG’s procurement team.

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