TikTok Trend Tracker

Videos

Tech Stack

Web3

Node

Java

Python

Rust

Description

Problem: Creators struggle to identify trending content early → miss chances to go viral.
Solution: AI-driven platform that tracks TikTok data (hashtags, sounds, videos) and suggests trends in real time.
Core Features:
- Trend detection dashboard (real-time insights).
- Content idea generator (hooks, captions, sound suggestions).
- Gamified rewards (NFT badges & tokens for trend adoption).
- Community leaderboard for creators.
Tech Stack: AI/ML (Python, LLMs), Web (React/Next.js), Blockchain (Polygon/Solana for NFTs & tokens).
Impact: Empowers small creators, accelerates growth, and builds a Web3-enabled creator economy.
Business Model: Freemium access, premium subscription for advanced analytics, marketplace for trend ideas.
Vision: Become the go-to platform for creators to catch trends early, grow fast, and get rewarded fairly.

Progress During Hackathon

Phase 1 – Month 1–2 (MVP Build) Research TikTok data sources & APIs. Build AI model to detect trending hashtags, sounds, and videos. Develop simple web dashboard to display top daily/weekly trends. Phase 2 – Month 3–4 (Core Platform) Add personalized content suggestions (caption, hook, sound). Launch creator leaderboard. Deploy Web3 integration: mint simple NFT badges for trend adoption. Alpha test with a small group of creators. Phase 3 – Month 5–6 (Growth & Rewards) Introduce token reward system for creators. Release mobile app (iOS/Android). Expand trend prediction (forecasting trends before they peak). Public beta launch. Phase 4 – Month 7+ (Scale & Monetization) Subscription model for advanced analytics. Creator marketplace for trading trend ideas & scripts. Partnerships with agencies/brands. Global rollout.

Fundraising Status

Currently bootstrapped, focusing on MVP development. Open to strategic partnerships and future seed funding