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FHS is a complete, indexed, and chain-agnostic dataset from genesis to tip used to power audits, research, analytics, and investment strategies with institutional-grade accuracy across 120+ blockchains. Everything you need to understand, model, and build with on-chain truth.

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Use Cases from real SonarX customers

1.      Forensics, Compliance, and Audits Review the complete history of blockchain transactions and transfers to ensure regulatory compliance, investigate suspicious activity, administer KYT and AML, and support legal investigations. 2.      Trading and Investing (decision support & back-testing) Use SonarX infrastructure to support both trading and research needs while maintaining data integrity, security, and performance at scale. Benefit from the ability to jump quickly and swiftly from chain to chain in search of Alpha, without re-inventing the wheel at every jump. 3.      Data Analytics and Research Platforms Power your data and research platform with fully indexed and comprehensive genesis-to-tip data for any chain. 4.      RWA Product Strategy and Marketing Take a data-driven approach to your Tokenized product’s strategy. Utilize high-quality on-chain data across any blockchain to inform decisions on where to launch your product, track usage and adoption, understand competitive products, and target specific wallets and pools of capital. 5.      Build Financial Indexes Utilize on-chain data to construct digital asset indices, encompassing fundamentals and total rewards, with the highest quality and complete history of staking reward data. 6.      Smart Contract Audits Trace the complete on-chain behavior history of any smart contract over time to inform an audit on new or similar smart contracts. 7.      Cross-Chain Provenance Tracking With 120+ blockchains covered, you can track the complete history of assets and activity across chains and ecosystems, which is essential in an increasingly chain-interoperable landscape. 8.      Staking Calculations Track the entire chain or specific validator staking activity over time with high-quality data to calculate staking rewards and performance accurately. 9.      ML Model Building Use historical data to train machine learning models for predictive analysis, forecasting, and risk or trading signals. 10.      Token and Protocol Research Study token supply fluctuations and perform detailed protocol analysis for long-term investment insights.