Abstract: The purpose of this paper is to develop a conceptual business model, called Fath, including a digital platform and Application Programming Interface (API) infrastructure, to solve key challenges regarding data privacy, vendor lock-in, and high inference costs faced by three Customer Segments (CS): (a) Privacy-First Enterprises and Small and Medium-Sized Businesses (SMEs), (b) High-security government agencies and corporations, and (c) AI Startups and cost-focused developers and researchers. Key pains include the prohibitive cost of proprietary APIs and the technical complexity of self-hosting open-source Large Language Models (LLMs). The paper adapts Design Thinking (DT) methodology that include conducting a literature review on Fourth Industrial Revolution (4IR) trends, benchmarking competitors such as OpenAI and AWS using the Business Model Canvas (BMC) framework and conducting surveys to define problems. An initial business model prototype was designed using the Environment Map (EM), BMC, and Value Proposition Canvas (VPC), followed by validation against market needs. Key findings indicate a significant gap for a "privacy-first," cost-effective inference provider. This paper establishes a validated business model where Fath serves as a gain creator by offering drop-in API compatibility with open-weights models. A Strategy Canvas (SC) is created to compare Fath against incumbent players, highlighting its relevance in solving extreme pains related to data sovereignty. Future work includes developing a detailed business plan and deploying the high-fidelity digital platform prototype.
Keywords: Fath, Open-Weights AI, AI Inference, Business Model, Data Privacy, Technopreneurship, API Economy, Large Language Models, Design Thinking.
Title: A Conceptual Fath Business Model: Digital Platform for Accessible, Private, and Open-Weights Artificial Intelligence Inference
Author: MUHAMAD HAZIM ISKANDAR BIN HASSAN NORDIN, MUHAMMAD SAFWAN BIN SAMSUDIN, MUHAMMAD ZULHARIZI BIN ZAFRAN, MUHAMMAD SHAZWAN SHAH BIN MOHD NORHADI SHAH, ABDUL RAHMAN BIN AHMAD DAHLAN
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
Vol. 14, Issue 2, April 2026 - June 2026
Page No: 203-215
Research Publish Journals
Website: www.researchpublish.com
Published Date: 02-June-2026
