The QUICK AI: A Modular Toolkit for Creative Automation

References

[1] Zhao, H., & Chen, F. (2024). Scaling AI-as-a-Service (AIaaS): Architectural Paradigms for Enterprise Deployment. International Journal of Cloud Computing and AI, 15(2), 101–118.

[2] Garcia, L., & Lee, S. (2024). Full-Stack JavaScript Frameworks for High-Throughput AI Applications: An Evaluation of the PERN Stack. Journal of Software Engineering and Practice, 19(4), 312–330.

[3] Williams, J. (2023). Modular Design and Microservices Integration in Contemporary AI Platforms. IEEE Transactions on Systems, Man, and Cybernetics, 53(8), 4501–4515.

[4] Orozco, R., & Li, Y. (2023). User Lifecycle Management and Authentication in Multi-Tenant SaaS: A Security Analysis. Security and Privacy in Computing, 10(1), 12–29.

[5] Patel, D., & Jiang, Q. (2024). Mitigating Algorithmic Bias in Generative Models: Ethical and Technical Safeguards for Commercial AI. AI & Ethics Journal, 4(3), 550–567.

[6] Martinez, A. (2023). The Black-Box Challenge: Designing for Transparency and Trust with Explainable AI (XAI). ACM Journal of Human-Computer Interaction, 29(6), 801–819.

[7] Dixon, C., & Singh, R. (2024). Optimizing Frontend Performance for AI Latency: Strategies for Client-Side Caching and Asynchronous Queues. Frontiers in Web Development, 20(2), 195–211.

[8] Thompson, S., & Foster, C. (2023). Subscription-Based Feature Gating: Technical Methodology for Entitlement Management in Full-Stack SaaS. Journal of Subscription Economics, 7(4), 45–62

[9] Smith, M., & Yang, H. (2024). Democratizing Access: The Role of Integrated AI Tooling in Lowering Barriers to Entry for Small Businesses. Entrepreneurship and Technology Review, 12(1), 77–93.

[10] Zhou, K., & Miller, B. (2023). Real-Time Performance and Asynchronous Task Offloading in Node.js Backends. International Journal of Computer Systems Science and Engineering, 38(5), 405–420.

[11] Taylor, K. (2024). Row-Level Security in PostgreSQL for Multi-Tenant AI-as-a-Service Architectures. Database Management Systems Quarterly, 11(3), 155–172.

[12] Lopez, J. (2023). Strategies for Customization and Reconfigurability in AIaaS Platforms for Diverse Industrial Applications. Applied AI Research, 14(1), 10–25.

[13] Klaus, A., & Werner, G. (2024). Growth Trajectories and Monetization Strategies of Top AI Startups: A Quantitative Study. Venture Capital and Innovation Review, 3(2), 98–115.

[14] Chen, L., & Wang, Y. (2023). Designing Interactive Environments for Practical Skill Development using Real-Time AI Feedback. Journal of Educational AI, 6(4), 301–318.

[15] Wu, Z., & Thompson, A. (2024). Trust via Comprehensive Testing (Jest/Playwright) in Full-Stack AI Deployment. Software Quality Assurance Today, 17(1), 88–105.

[16] Sharma, V., & Gupta, M. (2024). Performance Optimization of Next.js App Router for Server-Side Rendered Applications with High Data Fetching Requirements. Web Development Best Practices, 10(3), 250–268.

[17] Al-Hassan, M. R., & Zhang, F. (2025). Decentralized Identity and Verifiable Credentials in Secure Recruitment Systems: Enhancing Trustworthiness and Privacy. Journal of Distributed Ledger Technology, 8(1), 5–22

[18] Rodriguez, E., & Kim, H. (2023). Latent Diffusion Models (Stable Diffusion) for Commercial Content Generation: A Review of API Integration and Efficiency. Creative Computing and Graphics, 41(6), 710–725.

[19] Zhu, H., & Foster, C. (2024). Real-Time Error Monitoring and Log Management in Microservice Architectures (Sentry/LogDNA) for MLOps. International Journal of DevOps and System Reliability, 15(4), 480–499.

[20] Gonzalez, M., & Bhat, R. (2023). Governance and Ethical Frameworks for AI-as-a-Service: Addressing Data Privacy. Ethics in Technology and Governance, 5(2), 130–147.

@article{1716410,
      author = {Taha Ansari, Namrata Singh, Aadarsh Singh, Asmit Singh, Prof. Yugandhara Pande},
      title = {The QUICK AI: A Modular Toolkit for Creative Automation},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {10},
      pages = {1702-1707},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1716410.pdf},
      abstract = {Quick AI is a full-stack Software as a Service (SaaS) application developed using the PERN stack (PostgreSQL, Express, React, Node.js). It integrates multiple modular AI-powered tools, including features such as article generation and image manipulation. The platform aims to bridge the gap between theoretical knowledge and real-world implementation by providing a user-centric, end-to-end solution that delivers clear, real-time results and is scalable across various industries. The key objectives of this research include evaluating modern authentication and subscription billing systems (such as Clerk) to enhance security and user trust, documenting the integration of modular AI components within a full-stack architecture, and exploring community-driven features to improve user engagement. Overall, Quick AI represents a practical and deployable AI SaaS platform that is secure, flexible, and designed to address dynamic, real-world challenges.},
      month = {April},
      doi = {https://doi.org/10.64388/IREV9I10-1716410}
  }