Equity research and financial analysis, minus the grind. Valuein is the data + intelligence layer that makes analysts, researchers and quants effective on day one: screen, value, monitor and write the memo without fighting your data. Survivorship-free, PIT SEC facts + smart-money signals for 19,000+ US companies since 1993. Plug into your stack: AI agents (Claude/Cursor) via MCP 75 tools + 27 analyst workflows, the Workspace, or Python. Every number traces to its filing, no AI hallucinations.
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Maker
📌
Hey Product Hunt 👋
I'm Rainer, solo founder of Valuein.
I spent years watching funds pay over $50K/year per seat for data
that is, fundamentally, SEC EDGAR filings. Public. Free. And practically
unusable without a full data engineering team.
So I built the data team into a product.
One token, three ways to consume:
🐍 Python SDK — `pip install valuein-sdk`, then start generating alpha by running your SQL queries or the ones in our template repository. We add more every week.
🤖 MCP Server — point Claude / Cursor / Codex at mcp.valuein.biz/mcp and your agent gets 14 tools + 10 agentic SOPs (equity research brief, screen-and-shortlist, capital allocation profile, …).
📦 Bulk Data API — stream Parquet directly. Built for B2B partners.
What's new today:
✅ 105M+ facts across 18,000+ US entities (active + delisted).
✅ Insider Transactions (Form 4) — new
✅ Institutional Ownership (13F-HR / 13D / 13G) — new
✅ Point-in-time, survivorship-free, 1994 → present
✅ 11,966 raw XBRL (2026 US Taxonomy Code) tags standardized to ~300 canonical concepts.
🎁 For PH today and early adopters: 60 days of Pro at 50% discount (normally $49/mo) with code PRODUCTHUNT60 at checkout.
I'd love to hear:
• Quants — what data point is still missing from your workflow?
• AI builders — what agentic financial workflow would you build?
Rip me apart in the comments. I built this for you. 🙏
— Rainer