Artificial Intelligence LLM for smarter access to documentation – Public Management Summary

dc.contributor.authorGafirov, Alexander
dc.contributor.authorZoller, Anne-Sophie
dc.contributor.authorStoll, Fabian
dc.contributor.authorSelvakumar, Jayalakshmi
dc.contributor.authorTeklit, Dejen
dc.contributor.mentorWache, Holger
dc.contributor.partnerWorldline, Zürich
dc.date.accessioned2024-12-03T19:15:36Z
dc.date.available2024-12-03T19:15:36Z
dc.date.issued2024
dc.description.abstractHowever, the sheer volume and complexity of these manuals often make it challenging for software engineers to locate the information they need quickly and efficiently. This frequent need to seek assistance from the Worldline team is time-consuming, inefficient, and ultimately costly for both parties. Recognizing the need for a more streamlined and user-friendly approach, Worldline partnered with the FHNW to conduct a practical student project aimed at developing a solution that would empower software engineers to find the information they need within the documentation.
dc.identifier.urihttps://irf.fhnw.ch/handle/11654/48822
dc.language.isoen
dc.publisherHochschule für Wirtschaft FHNW
dc.spatialBasel
dc.subject.ddc330 - Wirtschaft
dc.titleArtificial Intelligence LLM for smarter access to documentation – Public Management Summary
dc.type11 - Studentische Arbeit
dspace.entity.typePublication
fhnw.InventedHereYes
fhnw.StudentsWorkTypeSemesterarbeit
fhnw.affiliation.hochschuleHochschule für Wirtschaft FHNWde_CH
fhnw.affiliation.institutBachelor of Science
relation.isMentorOfPublication9a5348f4-47b3-437d-a1f9-7cf66011e883
relation.isMentorOfPublication.latestForDiscovery9a5348f4-47b3-437d-a1f9-7cf66011e883
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