Automated tender processing

Machine learning algorithm for faster and better tender processing.

The challenge

Simplifying the complex process of (public) tenders in the HVAC construction space.

In der Bauindustrie spielen Ausschreibungen (= Ausschreibung für ein Projekt oder einen Teil eines Projekts) eine Schlüsselrolle im Beschaffungsprozess für größere Bauvorhaben. Insbesondere - aber nicht ausschließlich - bei Projekten, die von öffentlichen Institutionen kommen, ist der Ausschreibungsprozess durch komplexe Dokumentationen, uneinheitliche Standards und lange Wartezeiten für alle Beteiligten gekennzeichnet.

Da sowohl Viessmann als auch seine Partner (Anlageninstallateure) ständig mit den Fragen des Ausschreibungsprozesses konfrontiert sind, hat wattx nach einer Lösung gesucht, die die Situation für diese Akteure verbessert und erleichtert.

Our solution

A ML-empowered platform that automatically matches relevant products to "Leistungsverzeichnis" positions.

After analysing the whole tender process, the required documents, involved stakeholders, and existing online platforms that are used for public tenders, we concluded that the greatest value for Viessmann in the current environment has to come from a faster and less manual handling of tender requests - specifically the process of analysing and editing the hundred-page long “Leistungsverzeichnisse”. Due to the lack of standardisation in the document structure as well as the product descriptions, it is a task that has traditionally not been easy to automate. Based on our analysis, our long experience in applied machine learning, and recent advances in the technology made it now possible for a smart program to semi-automate this task. Consequently, we built a first prototype of the product to showcase its capabilities.

The outcome

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Viessmann was convinced of our initial analysis as well as our prototype, and gave us the greenlight to start developing an MVP that will enable the whole organization to improve their internal processes dramatically.

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