AI Modelling with Tacton CPQ
The development and maintenance of product models is one of the most demanding tasks when implementing and further developing CPQ solutions. Especially for complex, highly variant products, extensive product information, technical dependencies, variants, and configuration rules must be translated into structured model logic. With the AI Product Modeling Assistant, Tacton is presenting a new approach designed to significantly accelerate this process through generative AI.
The webinar “AI Modelling with Tacton CPQ” demonstrates how artificial intelligence supports the classic product modeling process and generates an initial structured foundation for a Tacton CPQ model from existing product information. Various data sources such as PDFs, Excel spreadsheets, technical specifications, CAD/BOM data, or existing legacy data can be used as a starting point. The AI analyzes this information and identifies, among other things, product structures, assemblies, modules, attributes, and dependencies.
A central part of the webinar is the practical demonstration of the AI Product Modeling Assistant. Using a concrete product example, it becomes clear how a CPQ product model is created step by step from existing technical documents. Instead of building the model completely manually from scratch, the AI generates an initial model structure that, according to Tacton, is often already about 70–80% complete. This allows modelers to focus more on functional review, optimizing model logic, and defining complex rules.
Furthermore, the webinar explains how existing models can be further developed and maintained with AI support. New product variants, features, attributes, or price changes can be adjusted in a targeted way, without having to manually implement every change in the model. This makes AI Modelling relevant not only for the initial creation of a product model, but also for the continuous development and maintenance of the product portfolio.
Another focus is on the interplay between AI and human expert knowledge. The AI does not replace the modeler, but instead acts as an intelligent co-pilot. All generated structures and changes remain visible and can be reviewed, corrected, and approved by experts before being transferred into Tacton CPQ. This is intended to combine speed and automation with the necessary functional control and governance.
The webinar is aimed in particular at Tacton modelers, product managers, design engineers, CPQ managers, and companies looking to make their product modeling more efficient. Participants will gain practical insight into the possibilities of the AI Product Modeling Assistant and learn how existing product data can be used for AI-supported modeling.
At the core of the webinar is the question of how the classic approach of “analyze product data → manually create model → define rules → test and maintain” can evolve into a more efficient process of “provide product data → generate AI model → review and refine → synchronize into Tacton CPQ.” The goal is to reduce modeling effort and implementation time while increasing coverage of complex product portfolios.
Notice: The webinar will be held in german, we will make an english translation available afterwards.
The webinar “AI Modelling with Tacton CPQ” demonstrates how artificial intelligence supports the classic product modeling process and generates an initial structured foundation for a Tacton CPQ model from existing product information. Various data sources such as PDFs, Excel spreadsheets, technical specifications, CAD/BOM data, or existing legacy data can be used as a starting point. The AI analyzes this information and identifies, among other things, product structures, assemblies, modules, attributes, and dependencies.
A central part of the webinar is the practical demonstration of the AI Product Modeling Assistant. Using a concrete product example, it becomes clear how a CPQ product model is created step by step from existing technical documents. Instead of building the model completely manually from scratch, the AI generates an initial model structure that, according to Tacton, is often already about 70–80% complete. This allows modelers to focus more on functional review, optimizing model logic, and defining complex rules.
Furthermore, the webinar explains how existing models can be further developed and maintained with AI support. New product variants, features, attributes, or price changes can be adjusted in a targeted way, without having to manually implement every change in the model. This makes AI Modelling relevant not only for the initial creation of a product model, but also for the continuous development and maintenance of the product portfolio.
Another focus is on the interplay between AI and human expert knowledge. The AI does not replace the modeler, but instead acts as an intelligent co-pilot. All generated structures and changes remain visible and can be reviewed, corrected, and approved by experts before being transferred into Tacton CPQ. This is intended to combine speed and automation with the necessary functional control and governance.
The webinar is aimed in particular at Tacton modelers, product managers, design engineers, CPQ managers, and companies looking to make their product modeling more efficient. Participants will gain practical insight into the possibilities of the AI Product Modeling Assistant and learn how existing product data can be used for AI-supported modeling.
At the core of the webinar is the question of how the classic approach of “analyze product data → manually create model → define rules → test and maintain” can evolve into a more efficient process of “provide product data → generate AI model → review and refine → synchronize into Tacton CPQ.” The goal is to reduce modeling effort and implementation time while increasing coverage of complex product portfolios.
Notice: The webinar will be held in german, we will make an english translation available afterwards.
