The United States is facing a persistent and rising “tax gap,” the discrepancy between taxes owed and taxes paid, that is a systemic failure of traditional retroactive audit procedures. As the complexity of digital financial transactions continues to expand, the Internal Revenue Service (IRS) faces serious hurdles from aging infrastructure in providing revenue assurance. In this research, we present a new technical framework, namely the "Smart-Tax Ledger", combining a permissioned blockchain (Hyperledger Fabric) and Gradient Boosted Decision Trees (GBDT) for the real-time tax compliance. This architecture facilitates the automation of tax withholding and remittance at the point of transaction, leveraging triple-entry accounting principles and smart contracts. Also, the use of Zero-Knowledge Proofs (ZKP) safeguards the integrity of the distributed ledger and preserves taxpayer privacy. This work presents a complete architectural design, mathematical modeling of fraud detection algorithms, and a debate on the policy implications of the adoption of a “compliance-by-design” paradigm. The system, which is supposed to reduce administrative cost, limit human mistake and fill the national revenue deficit by technical intervention.