FalconAI: Cloud-based Automatic Execution of AI Workflows

Mahmoud Ellouh; Radwan Jalali; Muhamad Felemban

doi:10.1109/FLLM67465.2025.11391001

FalconAI: Cloud-based Automatic Execution of AI Workflows

Mahmoud Ellouh^*
, Radwan Jalali
, Muhamad Felemban

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper, we introduce FalconAI, a cloud-based web application platform for automating the deployment of Artificial Intelligence (AI) workflows. Each workflow consists of one or more Machine Learning (ML) models. FalconAI consists of two components: front-end and back-end. The back-end uses virtualization, containerization, and container orchestration to support elastic resources upon the deployment of the workflows. We demonstrate the ability of FalconAI to run multiple AI models on multiple workflows, each of them in a separate pod. In our proof-of-concept implementation, FalconAI can support three pods simultaneously before the scheduling policy takes over to execute each pod sequentially one at a time.

Original language	English
Title of host publication	2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025
Editors	Kai Erenli, Christian Guetl, Yaser Jararweh, Jim Jansen
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	58-61
Number of pages	4
ISBN (Electronic)	9798331594091
DOIs	https://doi.org/10.1109/FLLM67465.2025.11391001
State	Published - 2025
Event	2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025 - Vienna, Austria Duration: 25 Nov 2025 → 28 Nov 2025

Publication series

Name	2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025

Conference

Conference	2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025
Country/Territory	Austria
City	Vienna
Period	25/11/25 → 28/11/25

Bibliographical note

Publisher Copyright:
© 2025 IEEE.

Keywords

AI Workflows
Cloud Computing
ML Models

ASJC Scopus subject areas

Language and Linguistics
Computer Science Applications
Software
Linguistics and Language

Access to Document

10.1109/FLLM67465.2025.11391001

Cite this

Ellouh, M., Jalali, R., & Felemban, M. (2025). FalconAI: Cloud-based Automatic Execution of AI Workflows. In K. Erenli, C. Guetl, Y. Jararweh, & J. Jansen (Eds.), 2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025 (pp. 58-61). (2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FLLM67465.2025.11391001

Ellouh, Mahmoud ; Jalali, Radwan ; Felemban, Muhamad. / FalconAI : Cloud-based Automatic Execution of AI Workflows. 2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025. editor / Kai Erenli ; Christian Guetl ; Yaser Jararweh ; Jim Jansen. Institute of Electrical and Electronics Engineers Inc., 2025. pp. 58-61 (2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025).

@inproceedings{77b041051cca4e5e943a7783f75a4cf3,

title = "FalconAI: Cloud-based Automatic Execution of AI Workflows",

abstract = "In this paper, we introduce FalconAI, a cloud-based web application platform for automating the deployment of Artificial Intelligence (AI) workflows. Each workflow consists of one or more Machine Learning (ML) models. FalconAI consists of two components: front-end and back-end. The back-end uses virtualization, containerization, and container orchestration to support elastic resources upon the deployment of the workflows. We demonstrate the ability of FalconAI to run multiple AI models on multiple workflows, each of them in a separate pod. In our proof-of-concept implementation, FalconAI can support three pods simultaneously before the scheduling policy takes over to execute each pod sequentially one at a time.",

keywords = "AI Workflows, Cloud Computing, ML Models",

author = "Mahmoud Ellouh and Radwan Jalali and Muhamad Felemban",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025 ; Conference date: 25-11-2025 Through 28-11-2025",

year = "2025",

doi = "10.1109/FLLM67465.2025.11391001",

language = "English",

series = "2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "58--61",

editor = "Kai Erenli and Christian Guetl and Yaser Jararweh and Jim Jansen",

booktitle = "2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025",

address = "United States",

}

Ellouh, M, Jalali, R & Felemban, M 2025, FalconAI: Cloud-based Automatic Execution of AI Workflows. in K Erenli, C Guetl, Y Jararweh & J Jansen (eds), 2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025. 2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025, Institute of Electrical and Electronics Engineers Inc., pp. 58-61, 2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025, Vienna, Austria, 25/11/25. https://doi.org/10.1109/FLLM67465.2025.11391001

FalconAI: Cloud-based Automatic Execution of AI Workflows. / Ellouh, Mahmoud; Jalali, Radwan; Felemban, Muhamad.
2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025. ed. / Kai Erenli; Christian Guetl; Yaser Jararweh; Jim Jansen. Institute of Electrical and Electronics Engineers Inc., 2025. p. 58-61 (2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Jalali, Radwan

AU - Felemban, Muhamad

PY - 2025

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N2 - In this paper, we introduce FalconAI, a cloud-based web application platform for automating the deployment of Artificial Intelligence (AI) workflows. Each workflow consists of one or more Machine Learning (ML) models. FalconAI consists of two components: front-end and back-end. The back-end uses virtualization, containerization, and container orchestration to support elastic resources upon the deployment of the workflows. We demonstrate the ability of FalconAI to run multiple AI models on multiple workflows, each of them in a separate pod. In our proof-of-concept implementation, FalconAI can support three pods simultaneously before the scheduling policy takes over to execute each pod sequentially one at a time.

AB - In this paper, we introduce FalconAI, a cloud-based web application platform for automating the deployment of Artificial Intelligence (AI) workflows. Each workflow consists of one or more Machine Learning (ML) models. FalconAI consists of two components: front-end and back-end. The back-end uses virtualization, containerization, and container orchestration to support elastic resources upon the deployment of the workflows. We demonstrate the ability of FalconAI to run multiple AI models on multiple workflows, each of them in a separate pod. In our proof-of-concept implementation, FalconAI can support three pods simultaneously before the scheduling policy takes over to execute each pod sequentially one at a time.

KW - AI Workflows

KW - Cloud Computing

KW - ML Models

UR - https://www.scopus.com/pages/publications/105035883476

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DO - 10.1109/FLLM67465.2025.11391001

M3 - Conference contribution

AN - SCOPUS:105035883476

T3 - 2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025

SP - 58

EP - 61

BT - 2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025

A2 - Erenli, Kai

A2 - Guetl, Christian

A2 - Jararweh, Yaser

A2 - Jansen, Jim

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 25 November 2025 through 28 November 2025

ER -

Ellouh M, Jalali R, Felemban M. FalconAI: Cloud-based Automatic Execution of AI Workflows. In Erenli K, Guetl C, Jararweh Y, Jansen J, editors, 2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025. Institute of Electrical and Electronics Engineers Inc. 2025. p. 58-61. (2025 3rd International Conference on Foundation and Large Language Models, FLLM 2025). doi: 10.1109/FLLM67465.2025.11391001

FalconAI: Cloud-based Automatic Execution of AI Workflows

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this