A4 Article in conference proceedings
Artificial Intelligence Procurement Assistant : Enhancing Bid Evaluation (2024)

Waseem, M., Das, T., Paloniemi, T., Koivisto, M., Räsänen, E., Setälä, M., & Mikkonen, T. (2024). Artificial Intelligence Procurement Assistant : Enhancing Bid Evaluation. In S. Hyrynsalmi, J. Münch, K. Smolander, & J. Melegati (Eds.), Software Business : 14th International Conference, ICSOB 2023, Lahti, Finland, November 27–29, 2023, Proceedings (pp. 108-114). Springer. Lecture Notes in Business Information Processing. https://doi.org/10.1007/978-3-031-53227-6_8

JYU authors or editors

Publication details

All authors or editors: Waseem, Muhammad; Das, Teerath; Paloniemi, Teemu; Koivisto, Miika; Räsänen, Eeli; Setälä, Manu; Mikkonen, Tommi

Parent publication: Software Business : 14th International Conference, ICSOB 2023, Lahti, Finland, November 27–29, 2023, Proceedings

Parent publication editors: Hyrynsalmi, Sami; Münch, Jürgen; Smolander, Kari; Melegati, Jorge

Place and date of conference: Lahti, Finland, 27.-29.11.2023

ISBN: 978-3-031-53226-9

eISBN: 978-3-031-53227-6

Journal or series: Lecture Notes in Business Information Processing

ISSN: 1865-1348

eISSN: 1865-1356

Publication year: 2024

Pages range: 108-114

Number of pages in the book: 514

Publisher: Springer

Place of Publication:  Cham

Publication country: Switzerland

Publication language: English

DOI: https://doi.org/10.1007/978-3-031-53227-6_8

Publication open access: Openly available

Publication channel open access: Open Access channel

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/93510

Abstract

In modern business, maintaining competitiveness and efficiency necessitates the integration of state-of-the-art technology. This paper introduces the Artificial Intelligence Procurement Assistant (AIPA), an advanced system co-developed with Solita, a Finnish software company. AIPA leverages Large Language Models (LLMs) and sophisticated data analytics to enhance the assessment of procurement call bids and funding opportunities. The system incorporates LLM agents to enhance user interactions, from intelligent search execution to results evaluation. Rigorous usability testing and real-world evaluation, conducted in collaboration with our industry partner, validated AIPA’s intuitive interface, personalized search functionalities, and effective results filtering. The platform significantly streamlines the identification of optimal calls by synergizing LLMs with resources from the European Commission TED and other portals. Feedback from the company guided essential refinements, particularly in the performance of ChatGPT agents for tasks like translation and keyword extraction. Further contributing to its scalability and adaptability, AIPA has been made open-source, inviting community contributions for its ongoing refinement and enhancement. Future developments will focus on extensive case studies, iterative improvements through user feedback, and expanding data sources to further elevate its utility in streamlining and optimizing procurement processes.

Keywords: business; competitive strength; efficiency (properties); enterprises; high technology; artificial intelligence

Contributing organizations

Ministry reporting: Yes

VIRTA submission year: 2024

Preliminary JUFO rating: 1