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Methodology

How we source and publish this data.

Last reviewed: July 2026. This page is updated whenever a data source, cadence, or enrichment process changes.

Argus HQ ingests FDA Warning Letters, drug recalls, drug approvals, and Form 483 inspection citations directly from FDA.gov and the openFDA API, publishes each as a page linking back to the primary source document, and layers on AI-generated analysis that is fact-check-gated against the source and clearly labeled as Argus HQ commentary, never presented as the verbatim FDA record.

Argus HQ publishes four streams of FDA enforcement and regulatory data. Every public page on this site traces back to one of the sources below — we do not publish unsourced claims, and every finding on a record page is attributed to the FDA document it came from. This page documents exactly where the data comes from, how often it refreshes, what our AI enrichment does and does not do, and where the coverage is currently incomplete.

What “Reviewed by Andy Gaber” means

Record pages on this site (Warning Letters, recalls, approvals, Form 483s) carry the line “Compiled by Argus HQ Research from FDA primary sources · Reviewed by Andy Gaber, Founder.” This section defines that claim plainly, because an undefined “reviewed by” line is exactly the kind of unfalsifiable trust signal we refuse to publish elsewhere on this site.

“Reviewed” here means pipeline-level review, not a per-page editorial read of all 1,800+ record pages before or after they publish — that would be physically impossible for a one-person team and we will not pretend otherwise. Concretely, it means:

  • The templates and the fact-check gate are Andy’s design and Andy’s responsibility. Every record page is generated from a small set of templates (Warning Letter, recall, approval, 483, company) that Andy built and maintains. The automated fact-check gate described above — which blocks any AI-drafted analysis that introduces a claim, name, or citation absent from the source document — is Andy’s gate, configured and tested by him, not a black box he is disclaiming.
  • A weekly spot-review, performed weekly. Each week, Andy reviews a sample of newly published record pages against their FDA source documents and against the Data Quality Dashboard and corrections queue for that week — roughly 15 minutes, checking for template regressions, misattributions, and any AI-summary drift the automated gate might have missed. This is a review of the pipeline’s output in aggregate, not a claim that any single page was individually read by a human before publication.
  • Every correction report is reviewed by Andy personally. The corrections process described below (email corrections@argushq.ai) is not outsourced or automated past triage — Andy reads every report against the source document and decides the fix.
  • Andy is a named, real, accountable person, not a synthetic persona or a fabricated team roster. See /about/andy-gaber for who he is and what he’s accountable for.

If you think a specific page’s “Reviewed by” claim doesn’t hold up — a summary that misstates its source, a template bug, anything — that is exactly what the corrections process exists to catch and log. This section itself is dated below and will be updated if the review process changes.

Data sources, by stream

FDA Warning Letters

Sourced from the FDA’s public Warning Letters listing at fda.gov. We scrape this listing daily at 04:00 UTC, diff it against what we’ve already ingested, and pull down any newly posted letters in full.

Drug recalls

Sourced from the openFDA drug enforcement endpoint, api.fda.gov/drug/enforcement.json. Our cron job queries this endpoint on a 10-day lookback window on every run, so a recall that posts late or gets amended by FDA is still picked up on the next cycle rather than missed permanently.

Drug approvals

Sourced from two openFDA endpoints: api.fda.gov/drug/drugsfda.json for approval records and api.fda.gov/drug/label.json for the associated label data. This is currently our newest and least complete stream — see Known limitations below.

Form 483 inspection observations

FDA does not currently offer a comprehensive public API for Form 483s. We source what we can from FDA’s public inspection databases, and we are disclosing openly that 483 coverage is pending an API key application with FDA and is materially incomplete today. Any 483 record we do publish is reproduced verbatim from a document FDA has already made public — we do not estimate, infer, or synthesize 483 content.

What our AI enrichment is, and isn’t

Every record page reproduces its FDA source document in full, verbatim. Above that, we add a short analysis section. That analysis section is AI-drafted directly from the source record and reviewed against an automated fact-check gate before it publishes. The gate checks the draft against the source document it was generated from and blocks publication if it introduces a claim, company name, or citation not present in the source. This means: the AI is a summarization and formatting layer, not an independent research process. It does not add outside facts, does not speculate about outcomes or intent, and does not offer legal, financial, or medical advice. If you ever find an analysis section that contradicts or misstates the underlying FDA document, that’s a bug — see Corrections below. The full legal terms of how we use AI, and what you need to independently verify, are in the AI Disclaimer.

Corrections

If you find an error — a misread date, a misattributed company, a broken source link, an AI-drafted summary that misstates the source document — email corrections@argushq.ai with the page URL and what’s wrong. We fix confirmed errors within 2 business days and add a dated correction note directly on the affected page. See the Editorial Policy for the full corrections process.

Known limitations

  • Form 483 coverage is pending. We do not yet have an FDA API key for inspection-citation data, and 483 records on this site are limited to what is separately public. This is the single largest coverage gap in the product today.
  • Drug approval coverage is partial. The approvals stream is the newest of the four and does not yet cover every NDA/ANDA/BLA action FDA has taken; we are expanding it incrementally.
  • Recalls reflect a 10-day lookback per run. A recall that FDA amends more than 10 days after its initial posting may not be re-captured until we widen that window.
  • Entity matching is automated and imperfect. We match companies named in enforcement records to entity profiles algorithmically. Misattribution is possible, particularly for companies with similar names or multiple corporate subsidiaries.

If the coverage gaps above mean Argus HQ isn’t earning its place in your workflow within your first 30 days, you’re covered by our 30-day money-back guarantee — see the Refund Policy for how that works.

See Data Sources for a table view of refresh frequency and fields captured per stream, and the Updates log for a running, dated record of what was added and when.

Dataset paper

For a citable, arxiv-style writeup of the dataset’s methodology, structure, and statistics, see the Argus HQ FDA Enforcement Dataset paper (PDF). Bulk licensing for enterprise use is described on the data licensing page.

Programmatic access

Every stream described above is also available programmatically — an MCP server for Claude/ChatGPT/Cursor, four per-entity JSON APIs, an OpenAPI 3.1 spec, and an llms.txt file. See /developers for install instructions and examples.