AI-supported assistant for tender management

The aim of the project was to support companies in identifying and evaluating relevant tenders. 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.

70% time saving

Automated search replaces manual searches on platforms

Higher hit rate

AI-supported profile matching precisely identifies relevant tenders

Better basis for decision-making

Tabular scoring display with KO criteria creates transparency

The results are presented to users in a clear tabular display that makes KO criteria, requirements and suitability visible at a glance. Users are also notified by e-mail as soon as new relevant tenders are found.

In a planned expansion stage, the wizard will expand its functionality to include support for preparing quotations, enabling companies to make the entire process from identification to submission of the quotation more efficient.

Challenge

The development of a tender assistant presented the project team with various technical and organizational challenges:

Heterogeneous platforms: Different interfaces and data structures required the parallel use of scraping mechanisms and APIs.
Regular updates: Tenders change dynamically, which made it necessary to continuously review them with a high degree of reliability.
Requirements comparison: Company profiles had to be recorded in a structured manner in order to be able to compare them with the tender requirements using AI.
Relevance assessment: The aim was to develop a scoring model that realistically assesses opportunities.

User-friendliness: Results had to be presented clearly and comprehensibly – for example in tabular form with KO criteria.
Notification: Users should be informed automatically without having to actively search themselves.
Quotation creation perspective: In the expansion stage, additional text generation and document creation functions had to be integrated.

Realization

The developed solution is based on a modular, AI-supported architecture that maps the entire tender management process – from data collection to analysis and automated evaluation. Tender platforms are connected via APIs or scraping technologies 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.

At its core is an LLM-supported analysis and scoring process 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. 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.

In addition, the system automatically informs users by e-mail as soon as new suitable tenders are available. In a further expansion stage, the integration of a tender assistant 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.

Automated data collection: Connection of tendering platforms via API or scraping for continuous updating.
AI-supported profile matching: LLMs compare tender requirements with company profiles and assess relevance.

Clear presentation of results: Tabular dashboard with scoring, KO criteria and direct links to tenders.
Proactive notification & expansion potential: e-mail alerts for new tenders and optional offer generation in the expansion stage.

Conclusion

The AI assistant for tender management impressively demonstrates how routine tasks can be automated and strategic decisions improved at the same time.

Companies benefit from a significant increase in efficiency in the search and evaluation process.
The user-friendliness ensures a high level of acceptance in everyday working life.
The scoring model creates an objective basis for decision-making.
The automation of notifications reduces response times.
The planned expansion stage for preparing quotations will further increase the benefits of the solution.

The assistant is thus evolving from an information filter into a strategic tool that provides companies with long-term support in the competition for tenders.

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.

Theresa Herbig, Chief of Staff & AI Initiatives, BITS GmbH

Project roles at a glance

BITS experts took on the following roles in this project.

IT-Consulting/Consulting
IT Project Management
IT and AI system architecture
RAG-Engineering

Fullstack development
Prompt/context engineering
Infrastructure / Operation
DevOps

Tools & Technologies

The following tools and technologies were used in this project.

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