StockFit API

StockFit API is a financial data platform built specifically for developers, quants, and research platforms who need direct, reliable access to SEC filing data without the usual compromises. If you have ever tried to build a financial model, run a backtest, or analyze company fundamentals using existing APIs, you have likely run into a frustrating choice: pay for cheap tiers that deliver inaccurate or incomplete data, or sign expensive enterprise contracts that drain your startup budget. StockFit fills that gap completely. The platform pulls financial data directly from SEC XBRL filings, meaning there is no derived middle layer and every single number is traceable back to its original filing. This gives you confidence that what you are modeling is accurate and auditable. StockFit covers fundamentals, ownership data, ETF and mutual fund exposure, insider transactions, and all types of filings. It handles complexities that other APIs ignore, such as amended filings, non-December fiscal years, and Q4 reconstructions from 10-K and 10-Q data. Beyond raw numbers, StockFit provides rich economic models per company including offerings, peers, operating levers, competitive advantages, flywheels, strategic initiatives, and failure modes. For ETF and mutual fund exposure, the platform models mandate, portfolio construction, costs, sensitivities, and use cases in an AI-friendly format perfect for LLM workflows. With over 250 million facts, 5 million filings, and daily updates, StockFit is built for serious financial analysis. The platform is designed to deliver standardized financials, sector-aware metrics, and source-cited economic models that are structured specifically for valuation work and backtesting. Every data point is model-ready, meaning you can plug it directly into your quantitative models without worrying about taxonomy drift or inconsistent naming conventions. StockFit is the infrastructure layer for anyone building financial applications, research platforms, or algorithmic trading systems that demand accuracy and transparency.

Direct SEC XBRL Data

StockFit pulls financial data directly from SEC XBRL filings with no derived middle layer. Every single number is traceable back to its original filing through source citations included in every API response. This means you can verify the accuracy of any data point and audit your models with complete confidence. The platform handles complexities like amended filings, non-December fiscal years, and Q4 reconstructions from 10-K and 10-Q data.

Standardized and Model-Ready Financials

The API delivers standardized financial statements including income statements, balance sheets, and cash flow statements that are consistent across all companies and time periods. There is no taxonomy drift, meaning the field names and definitions remain stable even as SEC reporting standards evolve. The data is structured for direct use in valuation models, backtesting engines, and machine learning pipelines without requiring extensive preprocessing.

Rich Economic Models

Beyond raw financial numbers, StockFit provides comprehensive economic models for each company. These include detailed analyses of company offerings, peer comparisons, operating levers, competitive advantages, flywheels, strategic initiatives, and failure modes. For ETF and mutual fund exposure, the platform models mandate, portfolio construction, costs, sensitivities, and use cases in an AI-friendly format optimized for LLM workflows.

Comprehensive Data Coverage

StockFit covers over 250 million facts from 5 million filings with daily updates. The platform includes fundamentals, ownership data, insider transactions, and all types of SEC filings. It provides sector-aware metrics that normalize data across different industries, making it easy to compare companies in different sectors. The data is updated daily to ensure you always have access to the latest financial information.

Quantitative Backtesting and Financial Modeling

Quantitative analysts and algorithmic traders can use StockFit to build and backtest financial models with confidence. The standardized, source-cited data eliminates the risk of using inaccurate or incomplete information that could invalidate model results. The platform handles complex scenarios like amended filings and non-standard fiscal years, ensuring your backtests reflect real-world conditions accurately.

Fundamental Analysis for Investment Research

Investment researchers and analysts can access reliable fundamental data for deep company analysis. The economic models provide context beyond raw numbers, including competitive advantages, operating levers, and strategic initiatives. The ETF and mutual fund exposure data helps researchers understand how major funds are positioned, enabling more informed investment decisions.

AI and Machine Learning Financial Applications

Developers building AI-powered financial tools can leverage StockFit's model-ready data and AI-friendly format. The structured economic models are designed for LLM workflows, making it easy to incorporate financial data into natural language processing applications, automated report generation, and AI-driven investment analysis systems.

Corporate Finance and Valuation Work

Corporate finance professionals can use StockFit for company valuation, M&A analysis, and financial due diligence. The standardized financials enable consistent comparisons across companies and time periods. The source-cited data provides the audit trail necessary for regulatory compliance and internal review processes.

How does StockFit ensure data accuracy?

StockFit pulls financial data directly from SEC XBRL filings, eliminating any derived middle layer that could introduce errors. Every data point includes source citations linking back to the original filing, allowing you to verify accuracy independently. The platform handles complex scenarios like amended filings and non-December fiscal years that other APIs ignore.

What types of financial data does StockFit cover?

StockFit covers a comprehensive range of financial data including fundamentals (income statements, balance sheets, cash flow statements), ownership data, insider transactions, and all types of SEC filings. It also provides rich economic models per company including offerings, peers, operating levers, competitive advantages, flywheels, strategic initiatives, and failure modes.

How often is the data updated?

StockFit updates its data daily, ensuring you always have access to the latest financial information. With over 250 million facts and 5 million filings in the database, the platform provides extensive historical data while maintaining current updates for ongoing analysis and modeling.

Is the data suitable for machine learning and AI applications?

Yes, StockFit is specifically designed for AI and machine learning workflows. The data is standardized and model-ready, with no taxonomy drift. The economic models are provided in an AI-friendly format optimized for LLM workflows, making it easy to incorporate financial data into natural language processing and automated analysis applications.