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Research US stocks — search SEC filings, hear earnings calls, and track 13F, insider & congress trades. Plus ALVIS, an AI analyst that cites every number.

CodeinCloud is the comprehensive IDE on the cloud by which you can connect your Live Servers through SSH Connection and your hosting directories with FTP access and Enjoy the Live Developments with beautifully designed code :)
Website, pricing, platforms and company facts side by side.
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| Website | equibles.com | codeincloud.net |
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| Company | Startup from Portugal · 1 - 9 employees · 2025 | — |
| Listed in | — |
In their own words, as submitted to SaaSHub.


Equibles is a US stock research platform that turns SEC filings, earnings calls, and regulatory disclosures into structured, verifiable data. Every US stock page includes: Financial statements and company-specific KPIs extracted from XBRL filings, with non-GAAP bridges Earnings calls with audio...
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What each product offers, as listed by its team.


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As answered by people managing Equibles and CodeinCloud.
Equibles's answer
Equibles extracts the answers raw data feeds skip — company-specific KPIs (subscribers, deliveries, ARPU…), forward guidance, and non-GAAP bridges — from SEC filings and earnings calls, and every figure is cited back to the source document.
The same dataset is available three ways: the website, ALVIS (an AI analyst that answers with charts and citations), and an MCP server + REST API so Claude, ChatGPT, or your own code can work with primary-source data directly.
Equibles's answer
Most market-data products stop at standardized statements and prices. Equibles adds the layer investors actually open filings for:
There is a usable free tier, and every number links back to the filing it came from.
Equibles's answer
Equibles started in 2025 from a simple frustration: AI assistants talk about stocks confidently while being disconnected from the primary sources. So we built the data layer first — pipelines that continuously ingest and structure SEC filings, earnings calls, and ownership disclosures — and then put ALVIS (an AI analyst) and an MCP server on top, so both people and their AIs get answers that cite the underlying document.
Equibles's answer
Equibles's answer
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