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- Vol. 5 Issue 3
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Zeno AI: A Firebase-Based Approach to Automated Advertisement Generation and Publishing
Authors
1 Professor, Shri, Ambabai Talim Sanstha’s Sanjay Bhokare Group of Institute, Miraj, Maharashtra, India. 2 3 4 5Ambabai Talim Sanstha’s Sanjay Bhokare Group of Institute, Miraj, Maharashtra, India.
Article Information
- DOI
- No DOI
- Published In
- Volume 5, Issue 3 (2026)
- Published Online
- September-December 2026
- Pages
- 709-714
- Article Type
- Original Article
- Check for updates
- No DOI available for cross-reference
Abstract
View PDFSmall businesses, individual creators and early-stage brands need advertisements for festive sales, product launches and promotions, yet often lack designers, copywriters or a video-production budget. Producing one advertisement normally involves several separate steps: branding, creative design, copywriting and publishing. This is time-consuming, costly and often results in inconsistent branding. This paper presents the development of Zeno AI, an AI-based advertisement generator built on the Firebase platform (Authentication, Firestore, Cloud Storage and Cloud Functions). The platform offers a single guided workflow in which users can generate a brand logo, an AI character or model, a matching background scene and an advertisement script in one fast generation cycle, review each element, assemble the approved elements into a finished image or short video, and publish or schedule it to linked social media accounts. Previous work in this field has largely focused on isolated design tools or standalone image generators, lacking an integrated, affordable pipeline from brief to published advertisement. Our project aims to reduce the effort of advertisement production by combining generative AI with human-in-the-loop review and direct publishing. The paper outlines the design considerations, development methodology, testing procedures and potential impact of the proposed solution, and discusses directions for future research.
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