viaNexus and SavaNet Launch Advanced U.S. Fundamentals Dataset Built for Modern Analytics and AI

New dataset transforms complex regulatory filings into standardized financial data accessible through high-performance APIs

viaNexus, the high-performance financial data platform, announced the launch of the SavaNet-viaNexus U.S. Normalized Fundamentals dataset, developed in partnership with financial analytics firm SavaNet. The new dataset converts complex corporate filings into a deeply standardized financial framework designed for modern analytics, financial modeling, and AI-driven workflows.

Corporate financial statements remain essential for investment research and valuation, yet the underlying regulatory filings are often inconsistent, fragmented, and difficult to analyze at scale. The new dataset addresses this challenge by transforming XBRL filings into a standardized financial taxonomy that preserves reporting detail while enabling reliable comparison across companies.

The dataset is built on SavaNet’s Modeling and Analytics Information Classification System (MAICS), a proprietary financial taxonomy developed over two decades by SavaNet founder Eric Linder, CFA, a former hedge fund portfolio manager and senior equity analyst at J.P. Morgan. The MAICS framework organizes more than 3,000 financial elements into a five-level hierarchy designed specifically for financial analysis.

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Combined with the viaNexus platform, the dataset is delivered through modern, high-performance APIs and agent-ready services, allowing developers, analysts, and fintech platforms to access normalized financial statement data without the heavy data engineering typically required to work with regulatory filings.

“The combination of the extreme as-reported detail of XBRL with the standardized hierarchical structure of the MAICS taxonomy delivers the best of both worlds,” said Eric Linder, CFA, Founder of SavaNet. “Working with viaNexus allows this data to be delivered in a modern infrastructure designed for both analysts and AI systems.”

“Financial filings contain an enormous amount of information, but unlocking their value requires both deep domain expertise and modern data infrastructure,” said Tim Baker, Co-Founder of viaNexus. “By combining SavaNet’s taxonomy with the viaNexus platform, we’re making high-quality normalized fundamentals immediately usable for research, fintech applications, and emerging AI-driven workflows.”

The initial release covers more than 3,000 U.S. companies, with five years of quarterly and annual historical data and more than 250 standardized financial fields across the income statement, balance sheet, cash flow statement, and derived financial ratios. This will expand to cover all Reg NMS stocks in the near term.  A deeper dataset containing the full MAICS taxonomy and additional analytical measures is also available.

The dataset supports a broad range of applications, including equity research, financial modeling, fintech platforms, and AI-driven analytical systems that require consistent, structured financial inputs.

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