Trendpup
Sniff out Avax gems before they moon 🚀
Created on 29th June 2025
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Trendpup
Sniff out Avax gems before they moon 🚀
The problem Trendpup solves
Problem It Solves
An AI-powered early detection system specifically designed for Avalanche (Avax) Chain meme coins, identifying promising tokens before significant price movement.
Our profit-sharing business model aligns incentives perfectly with users — we only earn when our users profit from our signals.
What Users Can Use It For
Our AI-powered system helps users:
- Discover high-potential Avax meme coins early — before major price surges, giving retail investors a critical edge.
- Automate token monitoring — eliminating the need to manually scan Telegram, Twitter, DEXs, and trackers across multiple platforms.
- Filter scams and rugpulls — using behavioral and on-chain analysis to detect red flags, making trading safer.
- Identify real community momentum — distinguishing organic growth from paid shills or bot activity.
- Level the playing field — by reducing information asymmetry traditionally exploited by insiders, whales, and snipers.
- Enter earlier for maximum ROI — ensuring users don't miss the small window of explosive growth most meme coins experience early on.
How It Improves the Status Quo
Traditional methods of discovering meme coins on the Avax Chain have major flaws:
- Discovering tokens after the pump = missed profits
- Manual research wastes time and is error-prone
- Hard to tell a genuine project from a scam
- Insiders and bots always move first
- Most tools can't separate real hype from fake
- Retail traders often miss the early-entry sweet spot
Our system solves all of this — and better yet, we only profit when you do.
TrendPup Project Architecture Flow
Component Breakdown
-
Hosting:
All services are hosted on EC2 for reliability and scalability. -
Frontend (Next.js):
Handles wallet connection, access control, and user interface.
Communicates with backend for data and AI features. -
Scraper:
Scrapes Dex Screener for Avalanche token data.
Scrapes Twitter for token-related tweets and sentiment. -
AI Analysis (AWS Bedrock):
Reads tweets and token data.
Determines risk score, investment potential, and provides rationale. -
Eliza Agent (AWS Bedrock + RAG):
Special AI agent with Retrieval-Augmented Generation.
Answers user queries with the latest token data and in-depth analysis.
Summary:
Your system ensures only paid users (on Avalanche) can access premium features. The backend aggregates real-time blockchain and social data, then leverages advanced AI (AWS Bedrock) for investment analysis and conversational intelligence, all orchestrated through a modern Next.js frontend.
Challenges I ran into
Challenges I Ran Into
- Faced difficulties adapting to new versions of Eliza, as significant changes were made compared to older versions.
- Encountered problems while connecting the knowledge base to Eliza, especially in implementing contextual knowledge retrieval.
- Had to learn AWS Bedrock and its APIs from scratch, which added complexity to the integration process.
Specific Hurdle
When switching from the old Eliza versions to the latest one, I discovered that much of the internal architecture and usage patterns had changed. The new documentation lacked clear examples on how to implement contextual knowledge integration.
How I Overcame It
I resolved the issue through trial and error, experimenting with various configurations and reviewing code samples from related projects. While this process took several hours, it eventually helped me get the knowledge base working within Eliza's updated system.
Tracks Applied (6)
Onchain Finance
DeFi & Web3 Agents
ElizaOS
Productivity & operations
ElizaOS
Build the Future of Web3 x AI with Amazon Bedrock
AWS
AWS Credits for all Hackathon winners and runner ups
AWS
Avalanche Track
Avalanche
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