How VeliSignal Works
1. Continuous Market Monitoring
VeliSignal leverages the VeliAgent AI, which continuously processes data provided by the community, including:
Market trends.
Technical analysis.
Social sentiment and emerging narratives. Using advanced AI techniques like sentiment analysis and pattern recognition, the system identifies projects with high growth potential based on real-time data.
2. Verification and Potential Assessment
Before promoting any project, VeliSignal ensures it passes through a robust verification process:
Community-Driven Vetting: Data from multiple users is cross-referenced to ensure accuracy and validity.
AI Validation: The platform’s algorithms assess key factors like project fundamentals, innovation, and community support.
This ensures that only verified projects with strong indicators of success are selected for promotion, ensuring that users receive actionable and trustworthy information.
3. Automatic Broadcasting
Once a project is identified, VeliSignal autonomously posts a detailed update on the project’s X account. These posts are carefully crafted to maximize clarity and engagement, enabling users to make informed decisions. The posts include:
A summary of the project’s potential.
Key metrics and insights that contributed to its verification.
Acknowledgment of community members whose data helped verify the project.
4. Real-Time Engagement and Updates
VeliSignal goes beyond a one-time notification:
Early Contributions:
Users who provide valuable insights about a project before it is promoted play a critical role in training VeliAgent’s AI. These contributors are rewarded with points, reflecting the value of their input in identifying the project’s potential.
Post-Promotion Inputs:
If new, valuable information about the project emerges after the initial post, VeliSignal automatically tweets it as a follow-up in the comment section of the original tweet.
This ensures ongoing engagement with the project while maintaining visibility.
Users contributing these late updates also receive Points, though at a reduced rate compared to early contributors.
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