AI-supported assistant for tender management<\/h1>\n<\/div>The aim of the project was to support companies in identifying and evaluating relevant tenders<\/strong>. The AI assistant developed regularly monitors various tender platforms, compares their requirements with the individual company profile and provides an automated assessment of relevance and chances of success<\/strong>.<\/p>\n<\/div>![\"AI](\"https:\/\/www.mybits.de\/wp-content\/uploads\/2025\/10\/KI_Assistent_Ausschreibungsmanagement_Title-1.png\" "\\"AI")
<\/span><\/div><\/i><\/span><\/div>70% time saving<\/h2><\/div><\/div>\nAutomated search replaces manual searches on platforms<\/p>\n<\/div><\/div><\/div>
<\/i><\/span><\/div>Higher hit rate<\/h2><\/div><\/div>AI-supported profile matching precisely identifies relevant tenders<\/div><\/div><\/div><\/i><\/span><\/div>Better basis for decision-making<\/h2><\/div><\/div>Tabular scoring display with KO criteria creates transparency<\/div><\/div><\/div><\/div><\/div>The results are presented to users in a clear tabular display<\/strong> that makes KO criteria, requirements and suitability<\/strong> visible at a glance. Users are also notified by e-mail<\/strong> as soon as new relevant tenders are found. <\/p>\nIn a planned expansion stage, the wizard will expand its functionality to include support for preparing quotations<\/strong>, enabling companies to make the entire process from identification to submission of the quotation more efficient.<\/p>\n<\/div><\/div><\/div><\/div><\/div>Challenge<\/h2>\n<\/div>The development of a tender assistant presented the project team with various technical and organizational challenges:<\/p>\n<\/div>
- <\/i><\/span>\n
Heterogeneous platforms<\/strong>: Different interfaces and data structures required the parallel use of scraping mechanisms and APIs.<\/p>\n<\/div><\/li>- <\/i><\/span>\n
Regular updates<\/strong>: Tenders change dynamically, which made it necessary to continuously review them with a high degree of reliability.<\/p>\n<\/div><\/li>- <\/i><\/span>\n
Requirements comparison<\/strong>: Company profiles had to be recorded in a structured manner in order to be able to compare them with the tender requirements using AI.<\/p>\n<\/div><\/li>- <\/i><\/span>\n
Relevance assessment<\/strong>: The aim was to develop a scoring model that realistically assesses opportunities.<\/p>\n<\/div><\/li><\/ul><\/div><\/div>- <\/i><\/span>\n
User-friendliness<\/strong>: Results had to be presented clearly and comprehensibly – for example in tabular form with KO criteria.<\/p>\n<\/div><\/li>- <\/i><\/span>\n
Notification<\/strong>: Users should be informed automatically without having to actively search themselves.<\/p>\n<\/div><\/li>- <\/i><\/span>\n
Quotation creation perspective<\/strong>: In the expansion stage, additional text generation and document creation functions had to be integrated.<\/p>\n<\/div><\/li><\/ul><\/div><\/div><\/div><\/div><\/div>Realization<\/h2>\n<\/div>The developed solution is based on a modular, AI-supported architecture<\/strong> that maps the entire tender management process – from data collection to analysis and automated evaluation. Tender platforms are connected via APIs<\/strong> or scraping technologies<\/strong> in order to continuously record current tenders. The data is collected centrally, cleansed and prepared in a structured form so that it can be used for further processing by the AI system. <\/p>\nAt its core is an LLM-supported analysis and scoring process<\/strong> that compares the requirements of the tenders found with the company profile. The system automatically evaluates how well your own services and references match the tender requirements and creates a relevance rating with clear prioritization<\/strong>. The results are presented to users in tabular form via a user-friendly dashboard – including KO criteria, opportunity assessment and a direct link to the original tenders. <\/p>\nIn addition, the system automatically informs users by e-mail<\/strong> as soon as new suitable tenders are available. In a further expansion stage, the integration of a tender assistant<\/strong> is planned, which uses LLMs to generate suggestions for tender content and pre-fill documents. This will turn the solution into an end-to-end tool for the entire tender management process – from identification to tender submission.<\/p>\n<\/div>- <\/i><\/span>\n
Automated data collection<\/strong>: Connection of tendering platforms via API or scraping for continuous updating.<\/p>\n<\/div><\/li>- <\/i><\/span>\n
AI-supported profile matching<\/strong>: LLMs compare tender requirements with company profiles and assess relevance.<\/p>\n<\/div><\/li><\/ul><\/div><\/div>- <\/i><\/span>\n
Clear presentation of results<\/strong>: Tabular dashboard with scoring, KO criteria and direct links to tenders.<\/p>\n<\/div><\/li>- <\/i><\/span>\n
Proactive notification & expansion potential<\/strong>: e-mail alerts for new tenders and optional offer generation in the expansion stage.<\/p>\n<\/div><\/li><\/ul><\/div><\/div><\/div>Conclusion<\/h2>\n<\/div>The AI assistant for tender management impressively demonstrates how routine tasks can be automated<\/strong> and strategic decisions improved<\/strong> at the same time.<\/p>\n\n- Companies benefit from a significant increase in efficiency<\/strong> in the search and evaluation process.<\/li>\n
- The user-friendliness<\/strong> ensures a high level of acceptance in everyday working life.<\/li>\n
- The scoring model<\/strong> creates an objective basis for decision-making.<\/li>\n
- The automation of notifications<\/strong> reduces response times.<\/li>\n
- The planned expansion stage for preparing quotations<\/strong> will further increase the benefits of the solution.<\/li>\n<\/ul>\n
The assistant is thus evolving from an information filter<\/strong> into a strategic tool<\/strong> that provides companies with long-term support in the competition for tenders.<\/p>\n<\/div><\/i>With this project, we have shown how AI can create real added value in day-to-day business. The tender assistant noticeably relieves teams by automating routine work and at the same time providing a better basis for decision-making. For us, this is another step towards using AI solutions in a targeted manner where they can sustainably increase productivity and competitiveness.<\/div><\/div><\/span><\/blockquote>![\"theresa](\"data:image\/svg+xml,%3Csvg%20xmlns%3D%27http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%27%20width%3D%27800%27%20height%3D%27800%27%20viewBox%3D%270%200%20800%20800%27%3E%3Crect%20width%3D%27800%27%20height%3D%27800%27%20fill-opacity%3D%220%22%2F%3E%3C%2Fsvg%3E\")
<\/span>Theresa Herbig<\/strong>, <\/span>Chief of Staff & AI Initiatives, BITS GmbH<\/span><\/span><\/div><\/div><\/div><\/div><\/div><\/div>Project roles at a glance<\/h2>\n<\/div>BITS experts took on the following roles in this project.<\/p>\n<\/div><\/div><\/div>\n
- <\/i><\/span>\n
IT-Consulting\/Consulting<\/p>\n<\/div><\/li>
- <\/i><\/span>\n
IT Project Management<\/p>\n<\/div><\/li>
- <\/i><\/span>IT and AI system architecture<\/div><\/li>
- <\/i><\/span>\n
RAG-Engineering<\/p>\n<\/div><\/li><\/ul><\/div><\/div>
- <\/i><\/span>\n
Fullstack development<\/p>\n<\/div><\/li>
- <\/i><\/span>\n
Prompt\/context engineering<\/p>\n<\/div><\/li>
- <\/i><\/span>Infrastructure \/ Operation<\/div><\/li>
- <\/i><\/span>DevOps<\/div><\/li><\/ul><\/div><\/div>
Tools & Technologies<\/h2>\n<\/div>The following tools and technologies were used in this project.<\/p>\n<\/div>
The aim of the project was to support companies in identifying and evaluating relevant tenders<\/strong>. The AI assistant developed regularly monitors various tender platforms, compares their requirements with the individual company profile and provides an automated assessment of relevance and chances of success<\/strong>.<\/p>\n<\/div> Automated search replaces manual searches on platforms<\/p>\n<\/div><\/div><\/div> The results are presented to users in a clear tabular display<\/strong> that makes KO criteria, requirements and suitability<\/strong> visible at a glance. Users are also notified by e-mail<\/strong> as soon as new relevant tenders are found. <\/p>\n In a planned expansion stage, the wizard will expand its functionality to include support for preparing quotations<\/strong>, enabling companies to make the entire process from identification to submission of the quotation more efficient.<\/p>\n<\/div><\/div><\/div><\/div><\/div> The development of a tender assistant presented the project team with various technical and organizational challenges:<\/p>\n<\/div> Heterogeneous platforms<\/strong>: Different interfaces and data structures required the parallel use of scraping mechanisms and APIs.<\/p>\n<\/div><\/li> Regular updates<\/strong>: Tenders change dynamically, which made it necessary to continuously review them with a high degree of reliability.<\/p>\n<\/div><\/li> Requirements comparison<\/strong>: Company profiles had to be recorded in a structured manner in order to be able to compare them with the tender requirements using AI.<\/p>\n<\/div><\/li> Relevance assessment<\/strong>: The aim was to develop a scoring model that realistically assesses opportunities.<\/p>\n<\/div><\/li><\/ul><\/div><\/div> User-friendliness<\/strong>: Results had to be presented clearly and comprehensibly – for example in tabular form with KO criteria.<\/p>\n<\/div><\/li> Notification<\/strong>: Users should be informed automatically without having to actively search themselves.<\/p>\n<\/div><\/li> Quotation creation perspective<\/strong>: In the expansion stage, additional text generation and document creation functions had to be integrated.<\/p>\n<\/div><\/li><\/ul><\/div><\/div><\/div><\/div><\/div> The developed solution is based on a modular, AI-supported architecture<\/strong> that maps the entire tender management process – from data collection to analysis and automated evaluation. Tender platforms are connected via APIs<\/strong> or scraping technologies<\/strong> in order to continuously record current tenders. The data is collected centrally, cleansed and prepared in a structured form so that it can be used for further processing by the AI system. <\/p>\n At its core is an LLM-supported analysis and scoring process<\/strong> that compares the requirements of the tenders found with the company profile. The system automatically evaluates how well your own services and references match the tender requirements and creates a relevance rating with clear prioritization<\/strong>. The results are presented to users in tabular form via a user-friendly dashboard – including KO criteria, opportunity assessment and a direct link to the original tenders. <\/p>\n In addition, the system automatically informs users by e-mail<\/strong> as soon as new suitable tenders are available. In a further expansion stage, the integration of a tender assistant<\/strong> is planned, which uses LLMs to generate suggestions for tender content and pre-fill documents. This will turn the solution into an end-to-end tool for the entire tender management process – from identification to tender submission.<\/p>\n<\/div> Automated data collection<\/strong>: Connection of tendering platforms via API or scraping for continuous updating.<\/p>\n<\/div><\/li> AI-supported profile matching<\/strong>: LLMs compare tender requirements with company profiles and assess relevance.<\/p>\n<\/div><\/li><\/ul><\/div><\/div> Clear presentation of results<\/strong>: Tabular dashboard with scoring, KO criteria and direct links to tenders.<\/p>\n<\/div><\/li> Proactive notification & expansion potential<\/strong>: e-mail alerts for new tenders and optional offer generation in the expansion stage.<\/p>\n<\/div><\/li><\/ul><\/div><\/div><\/div> The AI assistant for tender management impressively demonstrates how routine tasks can be automated<\/strong> and strategic decisions improved<\/strong> at the same time.<\/p>\n The assistant is thus evolving from an information filter<\/strong> into a strategic tool<\/strong> that provides companies with long-term support in the competition for tenders.<\/p>\n<\/div> BITS experts took on the following roles in this project.<\/p>\n<\/div><\/div><\/div>\n IT-Consulting\/Consulting<\/p>\n<\/div><\/li> IT Project Management<\/p>\n<\/div><\/li> RAG-Engineering<\/p>\n<\/div><\/li><\/ul><\/div><\/div> Fullstack development<\/p>\n<\/div><\/li> Prompt\/context engineering<\/p>\n<\/div><\/li> The following tools and technologies were used in this project.<\/p>\n<\/div><\/span><\/div>70% time saving<\/h2><\/div>
Higher hit rate<\/h2><\/div>
Better basis for decision-making<\/h2><\/div>
Challenge<\/h2>\n<\/div>
Realization<\/h2>\n<\/div>
Conclusion<\/h2>\n<\/div>
\n
![\"theresa](\"https:\/\/www.mybits.de\/wp-content\/uploads\/2025\/06\/theresa_bits.png\")
Project roles at a glance<\/h2>\n<\/div>
Tools & Technologies<\/h2>\n<\/div>