Manage tenders and RFQs in machine industry with artificial intelligence

In this webinar, we will demonstrate how to overcome the challenges to properly manage requirements from the RFQ/Tender phase to the engineering phase in an end-to-end solution.

For companies responding to RFQs/Tenders, the quotation process is complex and introduces a high level of risk. It is crucial to managing the requirements from the first touchpoint with external documents throughout the entire engineering process, including the collaboration of all related stakeholders. A major part of this scenario is the re-usage of existing know-how.

Typical challenges:

• Complex RFQ/Tender documents with a large number of requirements must be assessed in a short time and with high quality.
• Not properly identifying and managing risks reduce the margins and weaken competitiveness.
• Poorly tracked customer requirements tend to cause high non-conformance costs.
• Expert availability: Find suitable professionals to analyze and respond to tenders in a short time properly.
• Focus on the RFQs/tenders with the highest likelihood of resulting in profitable projects.
• Collaboration of all involved stakeholders and management of the continuous changes.

Learn how AI can help you in this process to collaborate best with your human intelligence.

In this webinar, we will show you:

• How to manage requirements and know-how from the initial RFQ/Tender phase throughout the entire engineering lifecycle in a smart platform.
• How deep-tech AI technologies can reduce complexity and risk and enable an efficient quotation process.
• How to reduce failure costs and improve the collaboration process for all stakeholders.