For technical manufacturers like REHAU, processing a bill of quantities is not simply a matter of finding a product name.

A single tender position can specify material, pressure rating, nominal diameter, standards, approvals and application requirements. Matching these specifications to the right product requires significant technical expertise.

REHAU uses Mercura to automate this process. Today, Mercura identifies more than 98% of relevant positions in incoming bills of quantities. When the AI selects a product, the match is correct in 90% of cases.

The result: around 40% less time spent processing tenders.

The challenge: Product matching requires deep technical expertise

REHAU handles tenders and bills of quantities containing large numbers of individual product specifications.

Before Mercura, much of the underlying research and product assignment was performed manually. Experienced employees had to interpret each relevant position, understand its technical requirements and identify the appropriate product from the REHAU portfolio.

What makes this difficult is the level of detail contained in each position.

A specification may combine requirements for material, pressure rating, nominal diameter, standards, approvals and intended application. Each parameter can influence which product is suitable.

The bottleneck was therefore not simply data entry. It was repeated technical product research performed by highly qualified employees.

From manual search to AI powered product matching

REHAU introduced Mercura to automate the repetitive part of this process while keeping technical experts in control.

When a bill of quantities enters Mercura, the AI analyzes the document, identifies the positions relevant to REHAU and suggests suitable products from the company's portfolio.

Employees review the proposed matches and approve the final selection.

Mercura currently identifies more than 98% of relevant tender positions. When the system selects a specific article, that product is correct in 90% of cases.

Instead of starting every position with a manual search, the sales team starts with an AI generated product recommendation.

40% less time spent processing tenders

The impact is visible in the daily workflow.

REHAU has reduced tender processing time by approximately 40%, while around 20 inside sales employees now actively work with Mercura.

The time saved shifts the role of experienced employees away from repetitive product assignment and toward the work where their expertise matters most: evaluating technical requirements and validating the final proposal.

At the same time, product knowledge becomes easier to apply across the wider team instead of depending exclusively on employees who have built up that knowledge over many years.

Why AI works particularly well for complex technical tenders

Tender automation becomes more valuable as product complexity increases.

Simple keyword search works when a customer names an exact article. Bills of quantities often work differently: they describe the technical properties a product must fulfill.

Mercura analyzes those requirements and uses them to identify suitable products from the supplier's own portfolio.

For technical manufacturers, this makes it possible to automate part of a workflow that traditionally depended on manual interpretation and extensive product knowledge.

REHAU's results show what this can look like in practice: more than 98% of relevant positions identified, 90% product match accuracy when an article is selected and around 40% less processing time.

AI supports the expert rather than replacing the decision

The final product decision remains with REHAU's employees.

Mercura handles the repetitive analysis and matching work and provides a recommendation. Experienced employees review the result and approve it.

This human in the loop approach combines faster tender processing with the technical judgment required for complex product portfolios.

What REHAU's implementation shows

For manufacturers processing large volumes of bills of quantities, the biggest automation opportunity is often not quote generation itself.

It is the work that happens before the quote: understanding individual tender positions and finding the correct products.

By automating that step, REHAU has reduced the amount of manual product research required from its inside sales team while preserving expert review.

Could the same workflow be automated in your sales team?

If your employees spend hours reading bills of quantities, researching technical specifications and matching positions to products, Mercura can evaluate how much of that process can be automated using your own product portfolio.

See how Mercura would process one of your real tenders.