On-Premise Artificial Intelligence as a Service for Small and Medium Size Setups
It provides a practical solution for small and medium-sized users seeking to democratize AI without third-party dependence, though it is incremental as it builds on existing AIaaS concepts.
The paper addresses the lack of open-source, user-friendly AI as a Service (AIaaS) solutions for small and medium-sized setups, proposing an on-premise approach that enables full data control and avoids vendor lock-in.
Artificial Intelligence (AI) technologies are moving from customized deployments in specific domains towards generic solutions horizontally permeating vertical domains and industries. For instance, decisions on when to perform maintenance of roads or bridges or how to optimize public lighting in view of costs and safety in smart cities are increasingly informed by AI models. While various commercial solutions offer user friendly and easy to use AI as a Service (AIaaS), functionality-wise enabling the democratization of such ecosystems, open-source equivalent ecosystems are lagging behind. In this chapter, we discuss AIaaS functionality and corresponding technology stack and analyze possible realizations using open source user friendly technologies that are suitable for on-premise set-ups of small and medium sized users allowing full control over the data and technological platform without any third-party dependence or vendor lock-in.