Amyloom, the Fundamental Data API

Introducing Amyloom: The API for Raw, Traceable SEC Filings

Today, we are launching Amyloom in Early Access to provide the missing infrastructure layer for modern finance. We built this API for the developers, analysts, and traders who demand what the market currently lacks: structured, as-reported SEC filing data that machines can actually work with.

We deliver cross-validated, traceable financial data with speed and precision.

You can request early access today at amyloom.com.

The Problem We Are Solving

Financial data APIs have existed for years, yet building with them remains painful. You often have to choose between managing fragile scrapers yourself or trusting third-party vendors with opaque data quality.

We built Amyloom to solve the four biggest challenges in financial data infrastructure:

  1. Up To Date Historical Database: Instead of building your own historical database or polling for updates, rely on ours. We maintain a complete, 30+ year historical archive and instantly index new filings as they arrive.
  2. Lightweight and Efficient JSON Delivery: We transform disparate filing formats (.xbrl, .html, .pdf, …) into lightweight, structured JSON objects. Whether you are building a Fintech app, a Hedge Fund model, or an AI agent, our data is formatted for immediate programmatic use.
  3. Error Free Data Through Cross-Validation: We ensure data integrity by cross-referencing machine-readable XBRL tags against the original PDF and TXT reports to verify that every number matches exactly what the company reported.
  4. Traceable Standardized Data (coming soon): We map As-Reported items directly to standardized line items, eliminating opaque reconciliations. We show you exactly which raw reported lines were aggregated to calculate the final value, so you can verify the data source.

Data Coverage & Capabilities

Amyloom provides access to every line item from 10-K, 10-Q, 10-K/A, 10-Q/A, and S-1 filings. We combine AI extraction with rigorous algorithmic cross-checks and Human-in-the-Loop (HITL) validation. The result is clean, structured JSON that preserves the original taxonomy, labels, and values.

Coverage and Features
  • 6,500+ US stocks with 30+ years of historical data.
  • Near real-time extraction: Data is available minutes after filings hit the SEC website.
  • Full traceability: Every number links back to the specific line item in the original filing.
  • Amendment tracking: We capture both original and amended filings with SEC acceptance timestamps.
  • S-1 access: Access to pre-IPO financials and risk factors.
  • Websocket API (coming soon): For instant streaming of filings as they are published.

Why Amendments Matter

When a company restates prior period financials, you need to know what changed, when it changed, and the magnitude of the correction. We capture both the original filing and the amended version, timestamped with SEC acceptance times. This allows you to update historical models accurately without erasing the past.

Use Cases

  • Investment Teams & Asset Managers: Build AI agents that understand what companies actually report. Automate quality of earnings analysis, screen for buried expenses in "other" line items, and benchmark segment-level unit economics.
  • Fintech Developers: Build features that differentiate your product. Create native AI assistants that cite their sources, deep screening tools that filter on segment-level margins, or risk monitors that flag specific balance sheet disclosures.
  • Quants and Traders: Ensure point-in-time accuracy. SEC acceptance timestamps prevent look-ahead bias in backtests. Track amendments automatically and build factor models on granular line items using exact integers, not rounded aggregates.

As-Reported vs. Standardized Data

The industry standardized financial data because human analysts needed comparability. If you compare Microsoft and Apple, you want their income statements to use the same labels.

But standardized APIs flatten the semantic richness of financial reports. When an API maps distinct line items like 'Litigation Reserves' or 'Restructuring Costs' into a generic 'G&A' bucket, the signal is entirely lost to analysts and LLMs.

Amyloom preserves the original semantic labels. This gives your pipeline the granular context it needs to detect anomalies and cite the exact source, rather than guessing based on normalized aggregates.

The Future of Standardization: Transparent Mapping

We are not against standardization; we are against opaque standardization.

Our Standardized Financials come with a key difference: full traceability.

Traditional vendors treat normalization as a black box. If you see a value for "Total Liabilities," you have to guess whether it includes "Lease Obligations" or "Pension Liabilities."

Because Amyloom starts with the As-Reported layer, our Standardized data is a transparent aggregation of those raw items. You won't just see the final number; you will see the exact list of original 10-K line items that were summed to create it. You get the comparability of standardized data with the auditability of raw filings.

Pricing & Beta Access

We designed Amyloom to support every stage of growth. At full launch, we will offer four tailored plans: Free (for hobbyists and sandbox testing), Individual ($99/mo) for researchers and traders, Professional ($999/mo) for investment firms powering internal research, and Commercial ($2,999/mo) for fintechs and banks building customer-facing apps.

However, during our Early Access Beta, we are opening the gates:

  • Free, Unrestricted Access: We are giving select beta testers full access to our complete datasets and API limits for free.
  • Beta Timeline:
    • January 2026: Website launch, beta registration opens.
    • Early February 2026: Datasets ready, beta access begins.
    • Q2 2026: Full API launch.
  • Launch Benefits: Beta users will secure a permanent discount on paid plans when we officially launch.

Our Commitment

At Amyloom, our core principle is: every number must be traceable to its source, validated, and usable for developers, analysts and AI-driven pipelines.

Financial markets run on information. For too long, that information has been locked in PDFs or buried in databases with quality issues. We are changing that.