Key points at a glance
- Quoting software for manufacturers reads tenders and matches every line item to a product from your own range.
- Published results range from 87% matching precision to up to 60% less manual quoting effort, depending on the product area.
- Metrics differ: precision, effort, research time and quoting cycle measure different things.
- A result becomes transferable only through a test with your own bills of quantities and a measured baseline.
As of 5 November 2026
Disclosure: this article is published by Scalera. All customer results come from scalera.ai (homepage, Product Matching) and each describes a single project. They are not a promise for other companies.
What is quoting software in construction?
Quoting software in construction turns incoming requests and bills of quantities into a quote you can review. For manufacturers and distributors, that mainly means recognising line items and matching them to their own range. Contractors, by contrast, use software that estimates their own work.
Modern solutions use AI for this. Scalera processes tenders in PDF, scan, Excel, GAEB, NPK, ÖNORM and other standards and matches line items based on specification, application context and standard, not just keywords (Scalera, Product Matching).
Which features does quoting software for manufacturers need?
Six features are at the core. The table names them briefly and points to the articles that cover each feature in depth.
| Feature | What it does | Read more |
|---|---|---|
| Intake | Reads BoQs in all common formats and languages | Analyse a BoQ with AI |
| Triage | Sorts by estimated contract volume, flags duplicates | Bid or no bid |
| Matching | Matches line items to large product catalogues | Product matching at scale |
| Rationale | Shows rationale and AI confidence for each suggestion | Pilot AI tender software |
| Accessories | Detects missing accessories, suggests add-ons | Accessories and add-ons |
| Export | Sends via CSV, XML, GAEB or API to ERP, CPQ, CRM | ERP integration |
Feature information according to Scalera, Product Matching, as of 5 November 2026.
What do manufacturers achieve by product area?
The results differ clearly, and not only in size. Each project reports a different metric. The overview below puts the figures published on scalera.ai side by side (Scalera, homepage, Scalera, Product Matching).
| Product area | Company | Result per project |
|---|---|---|
| Insulation and facade systems | Saint-Gobain | 87% matching precision |
| Valves, sensors, actuators | Belimo | up to 60% less manual quoting effort (DACH) |
| Hydraulic and drinking water | Oventrop Schweiz | over 55% less manual product research |
| Technical tenders | Sauter | around 45% time savings |
| Complex system builds | Baumit | up to 35% shorter quoting cycles |
| Concrete, cement, recycling | Holcim | measurably better win rates on large projects |
Source: customer results on scalera.ai and scalera.ai/en/product-matching, as of 5 November 2026. The figures come from individual projects and are not directly comparable.
Other companies describe their results without a percentage. Lindab automates standard and system configurations and analyses tenders more deeply for more precise offer positioning. Rockwool identifies requirements early through position-accurate tender analysis and gives more precise system recommendations.
Which metric measures what?
The six figures answer four different questions. Mixing them up means comparing apples with oranges.
- Precision: how many matches are technically correct? Example: 87% at Saint-Gobain. It measures quality, not time.
- Effort: how much manual work disappears per quote? Example: up to 60% at Belimo. It measures the whole processing step.
- Research time: how much shorter is the search for the right product? Example: over 55% at Oventrop Schweiz. It measures only one sub-step.
- Quoting cycle: how much faster does the quote go out? Example: up to 35% at Baumit. It measures lead time, including waiting times.
High precision can go together with a moderate time saving, for example when a lot of coordination with the customer remains. Conversely, faster research saves little if approval is the bottleneck. The article Pilot AI tender software shows how to measure these values in your own company.
Why do results differ by product area?
Three factors play a role here. They depend less on the software than on the product range and the incoming requests.
How structured are the bills of quantities?
Well-structured BoQs are easier to match than freely worded requests. Frauenthal, for instance, achieves over 90% precision on structured bills of quantities (Scalera, Frauenthal case study). Scans, drawings and mixed documents can require more review work.
How many variants does the range have?
The more similar items there are, the more technical attributes such as dimensions, standards or connection types matter. For a valve, the nominal size or the connection type alone can decide which item is right.
Are they single products or systems?
In system builds, one line item involves several components and accessories. The software then has to complete the system, not just find the main product. The article Accessories and add-ons in quotes describes how this works.
How should you read results stated by vendors?
With five follow-up questions that apply to every vendor, Scalera included. They turn a percentage into a statement you can assess.
- Which metric? Precision, effort, research time or quoting cycle.
- Which product area? A figure from insulation says little about valves or door systems.
- Which requests? Structured BoQs, scans or emails with free text.
- Compared with what? Which baseline and which previous way of working.
- How many cases? A single BoQ or operation over several months.
A vendor should be able to answer these questions. If an answer is missing, the figure is not wrong, but it is not yet transferable to your company.
Who works with quoting software in construction?
Manufacturers, dealers and general contractors, each with its own focus. Scalera describes its use for all three groups, from tender to ERP (Scalera, homepage).
- Manufacturers match BoQ line items to their own range and build quotes from them (Scalera, Product Matching).
- Dealers work with very large ranges from several suppliers, see AI for building materials distributors.
- General contractors assign line items and drawings to trades and suppliers and send RFQs (Scalera, Supplier Matching).
“With Scalera, we have significantly streamlined our administrative functions. Today, a central location is enough to optimally support the calculators and at the same time handle significantly more volumes.”
Ciril Disch, Head of Building Construction/Member of Management, HEW
How do you transfer results to your company?
By choosing the product area closest to yours and then measuring with your own data. These four steps are enough for a solid first assessment:
- Choose a reference: the published result with the most similar range and the same metric.
- Measure a baseline: how long your team needs per request today and how many requests are left unanswered.
- Test your own BoQs: typical requests from your daily work, including difficult scans and mixed formats.
- Measure the same way: the same metric as in the reference, otherwise the values do not match.
For companies that quote in several countries, the formats are worth a look. Scalera processes documents in all major European languages, including German, English, French, Italian and Spanish (Scalera, FAQ). More on GAEB, ÖNORM and NPK in the article tender formats.
Frequently asked questions about quoting software in construction
What is the difference between quoting software for manufacturers and for contractors?
Contractors use their software to estimate their own work for a bid. Manufacturers and distributors need software that matches line items from a bill of quantities to their products. The article CPQ vs. AI quote calculation separates the software categories.
What does matching precision mean?
Matching precision describes how many of the suggested product matches are technically correct. It says nothing about how much time a team saves. For any figure, ask whether it refers to the first suggestion or to a selection of several suggestions.
Are time savings and cost savings the same thing?
No. A time saving measures how much faster a task is done. Whether that becomes lower costs or more processed requests is up to your company.
Do published results also apply outside the DACH region?
Some figures refer explicitly to a region, for example Belimo's to the DACH region (Scalera, Product Matching). Scalera is used across Europe and processes documents in all major European languages (Scalera, FAQ). Whether a result transfers is best shown by a test with your own requests.
Which product areas can AI quoting software cover?
The examples published on scalera.ai range from insulation and facade systems through fastening, hydraulics, valves and actuators to concrete, cement and door systems (Scalera, homepage). What matters is less the industry than the quality of your product data, see Product data for tenders.
Does every product line need its own setup?
Product data is imported once. The knowledge then persists across teams and locations, so everyone works from the same information base (Scalera, Product Matching). Product data can be uploaded manually or connected via an interface (Scalera, FAQ).
Does quoting software also help general contractors?
Yes, with a different focus. For general contractors, Scalera assigns line items, drawings and attachments to the right trade and supplier and sends the RFQs (Scalera, Supplier Matching). The article Automate supplier price requests describes the process.
Key takeaways
- Quoting software for manufacturers and distributors matches BoQ line items to their own range; software for contractors estimates their own work.
- Published results range from 87% matching precision to up to 60% less quoting effort, depending on product area and metric.
- Precision, effort, research time and quoting cycle are different metrics and not directly comparable.
- BoQ structure, variant diversity and system products influence how high a result turns out.
- A figure becomes reliable only with your own BoQs and a measured baseline. In a demo, Scalera extracts relevant line items directly from your own BoQs.
Sources
- Scalera, homepage, customer results (Saint-Gobain, Sauter, Holcim, Baumit, Lindab, Rockwool), accessed 5 November 2026: scalera.ai/en
- Scalera, Product Matching (features, customer results Belimo and Oventrop Schweiz, 150+), accessed 5 November 2026: scalera.ai/en/product-matching
- Scalera, Supplier Matching (general contractors), accessed 5 November 2026: scalera.ai/en/supplier-matching
- Scalera, FAQ (languages, product data), accessed 5 November 2026: scalera.ai/en/faq
- Scalera, Demo (line items from your own BoQs), accessed 5 November 2026: scalera.ai/en/demo
- Scalera, Frauenthal case study (over 90% precision on structured BoQs), accessed 5 November 2026: scalera.ai/en/case-study/frauenthal
