A construction project follows a strict hierarchy. The client or the building owner is the client of the project, the construction management, architect and engineer are responsible for the planning and construction companies for the execution, i.e. the construction of the project. Depending on the project, more or fewer construction companies are involved, for example, from the construction company, which is responsible for excavations, to masons for the shell, to carpenters, electricians and plumbers for interior finishing and so on and so forth. The bigger the project, the more construction companies are usually involved, the more construction companies try to get the job. In the construction industry, everything initially revolves around tenders or tender documents. The tender documents are used to request bids from various construction companies in a standardized form and in an electronic standard. So far, so good. But if a construction company, which is often the case with SMEs, lacks this electronic standard, it also lacks the direct interface for smooth processing. Intelligent, AI-based OCR (Optical Character Recognition) steps into the breach and pulls the cart out of the mud so that the tender documents can nevertheless be processed without any ifs and buts.

It is common practice to obtain quotations from various companies for comparison purposes for individual construction services. This requires tender documents, which consist partly of plans and partly of a bill of quantities. This bill of quantities, also known as a devi (in German speaking places), serves as a tender document with standard items, which logically should facilitate the overview of the various works. Each individual work step for an overall service is described in detail in the devi. The next step is for the construction management to request bids from various construction companies. The devi serves as the basis for price quotations and its ultimate aim is to obtain a detailed cost proposal for the various overall services. The construction management now needs, for example, a road 250 meters long for access X to the planned building and invites tenders for this project from various civil engineering companies. The various road construction companies, in turn, now make further use of the tender documents to inquire themselves with their suppliers what pavement in this form with surface layer of thickness centimeter Y costs for 250 meters. Thus, these tender documents are sent back and forth, filled out and sent back and forth again, based on the electronic standard. Finally, the tender documents end up back at the construction management for their evaluation and cost comparison with all the offers received. Finally, the contract is awarded by the site management to one of the road construction companies.

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Intelligent OCR where electronic standard is missing

Depending on the status quo of progress in a construction company, however, precisely this electronic standard is completely missing. This is where the problems start with the processing of the tender documents. If these are now received in PDF format instead of an XML file, for example, suddenly everything has to be laboriously typed out by hand and entered into a system. This is not only annoying for employees and makes the work even more error-prone, but also represents an unnecessary disruptive factor in the entire workflow of the tendering process. In a worst-case scenario, this deficiency even deprives a construction company of an important contract. To prevent such frustration from arising in the first place, intelligent, AI-based OCR (Optical Character Recognition) comes to the rescue for construction companies that lack the electronic standard for processing tender documents. The OCR automatically extracts all relevant data from the documents in a matter of seconds, converts it and also prepares it immediately so that it can be used for further processing. Thanks to the intelligent software, in the future the electronic and automatic processing can be guaranteed for these documents, despite the fact that they are received in PDF (or other) format.

With the integration of intelligent, AI-based OCR, even construction companies without the electronic standard will no longer lag behind and will process devis automatically and efficiently without further complications. For SMEs in particular, this represents a massive relief in the complex and highly competitive processes of tendering procedures.