
FEATURED · DATA INFRASTRUCTURE
Why AI Agents Need a Trusted Data Layer
Half of new web articles are now AI-written and their citations often don't hold up. A trusted data layer gives agents structured, cited SEC filings to read before the noise.

FEATURED · DATA INFRASTRUCTURE
Half of new web articles are now AI-written and their citations often don't hold up. A trusted data layer gives agents structured, cited SEC filings to read before the noise.

We read 550 bank, broker and insurer 10-Ks: 84% now mention AI, and most AI risk factors flag vendors or data leaks. What on-prem, VPC and SaaS each fix.

We joined every Q2 2026 Form 4 with Q1-to-Q2 13F holder counts for 3,985 companies. Where insiders clustered their buying, institutions were more often leaving.

We measured every Q2 2026 13F: 66% of reported value landed in the three days before the Aug 14 deadline, and the raw filings need repair before use.

A hands-on walkthrough: query earnings call transcripts from Claude over MCP or from your code over REST, and get back cited passages, not summaries.

financialdatasets.ai, FMP, Massive, EODHD and FocusAlpha all call themselves financial data APIs. What each actually covers, costs, and is built for.

There is no Asian EDGAR. Japan splits EDINET and TDnet, Korea has DART, Taiwan MOPS — why extending US research into Asia is an integration problem.

Earnings call sentiment analysis with LLMs breaks on hedged, forward-looking language. Where models fail, and why cited transcript passages beat a score.

What a SEC filings API needs before AI agents can rely on it: EDGAR's real constraints, the failure data on retrieval pipelines, and a seven-point checklist.