Ai Viral
Freemium
Indie SaaS founders shipping with tools like Lovable or Cursor
LLMs will invent revenue figures with the same confidence they cite real ones — and when you're vetting a position from a 10-K, a hallucinated number is worse than no number at all. Sharpread separates the two problems: AI reads the language, SEC XBRL data supplies every figure.
The core workflow is a single ticker input that returns a tear sheet covering red flags with verbatim filing quotes, XBRL-sourced financials, and a verdict. Every flagged claim links directly to the highlighted paragraph on EDGAR — so you can verify the citation in seconds rather than hunting through a 200-page PDF. The narrative drift feature lets you backtrack across quarters to see which risk disclosures were quietly dropped or softened. The ceiling arrives when you need to interrogate something outside the 10-K and 10-Q universe or run analysis at scale — the free tier caps at 10 lifetime analyses, and the paid tier is capped per month with top-up credits available.
Bottom line: Use Sharpread to pressure-test a long thesis against SEC filings before you size a position; plan a different workflow if you need bulk screening across a large universe or analysis of filing types beyond 10-K, 10-Q, and 8-K.
Run 10 free analyses. Enough to see QoQ work across two quarters.
For active analysts and investors.
If you need more than 50 in a month.
View full pricing on sharpread.ai →
Pricing may have changed since last verified. Check the official site for current plans.
Find your fit
More options in Business. Compare pricing, platforms, and features side by side.
Freemium
Indie SaaS founders shipping with tools like Lovable or Cursor
Freemium
Marketing teams running social ad campaigns
Sharpread takes a ticker, pulls the corresponding 10-K or 10-Q from EDGAR, and returns a structured tear sheet inside 30 seconds. Financials come directly from the SEC’s XBRL structured data — the numbers the company itself filed — so no AI model is inferring or rounding a revenue figure. The language layer uses Claude to classify management text across risk factors and MD&A, flagging hedge language, defensive framing, and unsupported assertions. Every red flag surfaces with the verbatim sentence from the filing and a direct link to that paragraph on EDGAR.
The differentiating architectural choice is the hard separation between text analysis and number sourcing. The vendor’s stated reason for building Sharpread was a failure mode encountered with general-purpose LLMs: plausible-sounding revenue figures that did not exist in the filing. By routing all financial figures through XBRL and all citations through EDGAR paragraph links, Sharpread closes the hallucination path on numbers — if the source sentence is absent from the filing, the claim is dropped rather than generated.
For the 8-K monitoring feature, you add a ticker to a watchlist and receive an alert when an 8-K publishes, including severity, a signal summary, and the verbatim key quote. Auditor resignations and late filing notices are automatically classified as HIGH severity. The quarter-on-quarter narrative drift feature requires backfilling historical filings and shows exactly where language was added, removed, or toned down between reporting periods — which is the kind of signal that rarely appears in a screener but regularly precedes a guidance cut.
The tool does not expose an API and has no self-hosted option, so it sits outside any automated pipeline. Analysis volume is constrained by credit tiers rather than rate limits, and earnings call analysis with Q&A evasion detection is a paid-only feature.
Sign in to rate this tool or suggest an edit.