Blockchain Augmented Crypto Asset Valuation: A June 2026 Milestone
The groundbreaking “Blockchain augmented crypto asset valuation apparatuses, processes and systems” patent was officially secured by FMR LLC. You can learn more about the company’s initiatives at their official website: https://www.fidelity.com/. This cutting-edge invention represents a major leap forward in how digital assets, including NFTs, are assessed by combining historical blockchain data with advanced artificial intelligence to establish reliable and continuously updating pricing models.
This invention was rightfully awarded the “Patent of the Month” for the ai-software-crypto-cloud industry for June 2026 because it introduces an unprecedented solution to the persistent problems of illiquidity and pricing opacity in the digital asset market. It is highly innovative because it utilizes dynamic AI crypto asset valuation engines capable of computing default, higher, and lower band valuations concurrently. The system is designed to automatically select the best-performing AI model for real-time accuracy. This unique convergence of machine learning, secure cloud-based data processing, and blockchain immutability effectively brings institutional-grade financial rigor to the decentralized crypto ecosystem.
R&D Tax Credit Implications for Practical Application
The practical applications of this patent involve intensive software engineering and system architecture that are highly likely to qualify for the Research and Development (R&D) tax credit in the United States under IRC Section 41. To commercialize the concepts in this patent, a company’s development teams must build, train, and refine complex AI valuation algorithms while successfully integrating them with decentralized blockchain ledgers. These activities fit squarely into the IRS’s four-part test: the work relies heavily on hard sciences (computer science and data engineering), it is intended to create a new or improved software function, it involves eliminating technical uncertainty (e.g., determining the most accurate algorithmic method to parse real-time transaction inputs against historical data), and it requires a systematic process of experimentation (iteratively testing AI models to achieve optimal valuation bands). Consequently, the wages, cloud computing costs, and engineering hours dedicated to designing, coding, and deploying these blockchain-augmented valuation systems could yield substantial dollar-for-dollar federal and state tax savings.
