TokenUnlocks provides a data analytics dashboard that tracks upcoming token emissions and vesting schedules, enabling users to analyze tokenomics across various projects. This platform addresses the need for transparent and actionable insights in the rapidly evolving cryptocurrency market.
Funding
Funding not disclosed
Founders
Product
Problem
The cryptocurrency market lacks transparency regarding token release schedules, making it difficult for investors to assess potential inflationary pressures and make informed decisions. Incomplete or scattered information on vesting schedules and token allocations hinders accurate supply-side analysis.
Solution
TokenUnlocks is a data analytics platform that provides comprehensive insights into tokenomics by tracking upcoming token unlocks and vesting schedules across various crypto projects. The platform aggregates and standardizes token release data, offering users a clear view of future token emissions. By comparing token allocation models and analyzing on-chain claims, TokenUnlocks enables investors and analysts to evaluate the potential impact of token unlocks on market dynamics. The platform's dashboard presents key metrics such as cliff unlocks, linear releases, and total weekly crypto market emissions, empowering users to make data-driven decisions.
Target Audience
The primary target audience includes cryptocurrency investors, traders, analysts, and researchers who require detailed insights into tokenomics and supply-side dynamics to inform their investment strategies.
Features
- Real-time tracking of token unlock schedules, vesting periods, and token allocations
- Aggregated data on cliff unlocks, linear releases, and total crypto market emissions
- Comparison tools for analyzing token allocation models across different projects
- On-chain claims data to track the actual movement of unlocked tokens
- API access for integrating token unlock data into custom analytical tools
- Emission Screener to filter projects based on user defined criteria
- CSV export functionality for offline analysis and reporting