Dörfler, Viktor
ORCID: https://orcid.org/0000-0001-8314-4162, Dylan, Dryden and Viet, Lee
(2025)
Intanify AI Platform: Embedded AI for Automated IP Audit and Due Diligence.
In: 39th AAAI Conference on Artificial Intelligence, 2025.02.25-2025.03.04, Philadelphia.
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Official URL: https://drive.google.com/file/d/1P2oWASX0hkYFHCATIjiWhX9UXfWOBYDQ/view
Abstract
In this paper we introduce a Platform created in order to support SMEs' endeavor to extract value from their intangible assets effectively. To implement the Platform, we developed five knowledge bases using a knowledge-based ex-pert system shell that contain knowledge from intangible as-set consultants, patent attorneys and due diligence lawyers. In order to operationalize the knowledge bases, we developed a "Rosetta Stone", an interpreter unit for the knowledge bases outside the shell and embedded in the plat-form. Building on the initial knowledge bases we have created a system of red flags, risk scoring, and valuation with the involvement of the same experts; these additional systems work upon the initial knowledge bases and therefore they can be regarded as meta-knowledge-representations that take the form of second-order knowledge graphs. All this clever technology is dressed up in an easy-to-handle graphical user interface that we will showcase at the conference. The initial platform was finished mid-2024; therefore, it qualifies as an "emerging application of AI" and "deployable AI", while development continues. The two firms that provided experts for developing the knowledge bases obtained a white-label version of the product (i.e. it runs under their own brand "powered by Intanify"), and there are two completed cases.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Series Name: | Proceedings of the AAAI Conference on Artificial Intelligence |
| Series Number / Identification Number: | MTMT:36058343 |
| Divisions: | Corvinus Institute for Advanced Studies (CIAS) Institute of Strategy and Management |
| Subjects: | Automatizálás, gépesítés Computer science |
| Funders: | INNOVATE UK |
| Projects: | No. 10052286 |
| ID Code: | 13132 |
| Deposited By: | MTMT SWORD |
| Deposited On: | 24 Aug 2026 11:48 |
| Last Modified: | 24 Aug 2026 11:48 |
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