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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM60177
Volume:
10 |
4 |
April 2026
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Building and maintaining a consistent online presence is harder than it looks. Between chasing trending topics, scripting videos, designing eye-catching thumbnails, and writing SEO-friendly blog posts, most independent creators simply run out of hours in the day. TrendNest AI was built to tackle this problem directly. It is a full-stack web platform that pulls live trend data from Google Trends and then uses a combination of Groq’s Llama 3.3-70B and Google Gemini to automatically produce YouTube video scripts, thumbnail images, and structured blog posts—all from a single interface. Raw trend titles are often too vague to feed directly into a generation pipeline, so the system first enriches them with a short AI-generated summary before passing the context downstream. Finished assets are stored in PostgreSQL through Prisma ORM, and thumbnail images are offloaded to Cloudinary for fast CDN delivery. The whole thing runs on Next.js 15 with TypeScript and is locked behind NextAuth.js session authentication so that only logged-in users can trigger generation. In testing, script generation averaged under four seconds, blog articles came back fully structured with clean HTML previews, and thumbnails consistently matched the visual style requested. The net result is a platform that meaningfully cuts the time it takes a solo creator or small marketing team to go from “what’s trending today” to publish-ready content.
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Publication Date
4/23/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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