Show HN: Corporate Hierarchy API – Map the corporate family tree

[mfrye0]

Hey HN! I'm sharing our Corporate Hierarchy API that we just launched in beta. Its current focus is on mapping the complete corporate ownership upwards to the ultimate parent by doing deep research across the open web and global government registries.

The problem: Companies spend millions on manual research teams to answer compliance / risk questions like, "does this business roll up to a state owned entity in China / Russia?". A bankruptcy processor we work with had 30 people just manually researching data points like this. An ex-Shell trader told us Shell has 800 people + $100M/yr spent with Deloitte to conduct manual research to ensure international trade compliance.

Why existing solutions are lacking: The dirty secret is that legacy providers like Dun & Bradstreet, Orbis, and S&P run on armies of manual workers and are built on decades old technology. At query time, you’re typically tapping into a quarterly generated, static, expensive database.

Our approach: We built this on top of our entity resolution engine - a deep research agent that anchors entities to our business graph, powered by direct integrations with government registrars and our web scraping infra. When you need hierarchy research, our AI agents spend on average 10-20 mins researching upward to identify the ultimate parent and build the complete ownership DAG with source citations. We auto-generate Mermaid diagrams so you can immediately render the results in your own app.

Technical backstory: I've spent 10 years building MDM, data enrichment, and entity resolution systems at B2B startups and enterprises, mostly in fintech. I actually built an in-house Clearbit replacement after they overcharged us and almost killed the startup I was at. The core challenge is always the same - taking messy business data and mapping it to web data and the actual legal entity. Most off the shelf solutions are mediocre because they skip the hard part: the gnarly 20-40% of records that force you into manual research.

Current state: Just three of us, bootstrap funded. We're getting requests for full subsidiary mapping too, but focused on upward hierarchy for now. We're still figuring out pricing (market rate seems to be a few dollars a lookup, but we aim to be a fraction of that). Deep research is expensive but we think we can make it work at scale.

Try it:

- Interactive demo: https://savvyiq.ai/products/entity-hierarchy (no signup)

- Free account: https://savvyiq.ai/signup

- API docs: https://savvyiq.ai/api-reference#tag/entity-hierarchy-beta

Would love feedback on the hierarchy API specifically, including the schema, gaps / edge cases, but also curious about other use cases where business identity resolution is a pain point for you.

Happy to run a few entity hierarchy lookups in the comments if anyone wants to see the API in action - I can share the results as Mermaid diagrams that you can paste directly into any Mermaid renderer.

[consumer451]

Thanks for mentioning this in a more recent comment. This might be very valuable for one of the projects that I am working on. Instant sign-up.

HN posts are such hit and miss. Do not be discouraged, this looks great.

As an example of HN hit and miss, I just posted a link to a reddit post regarding Claude Code, that could collectively save HN users many millions of dollars in the next week, and it has three upvotes at time of writing:

https://news.ycombinator.com/item?id=45723955

[mfrye0]

Thanks. I've been heads down on this for some time and don't have the huge network to share this with.

Regarding the product, I'm open to any and all feedback for your use case. Trying to follow the adage of "if you are not embarrassed by the first version of your product, you’ve launched too late".

And wow - just read your reddit post. I'm going to look into that for us too.

[windex]

Hey, this is very useful. I worked in a couple of large consulting firms and this type of entity search was a deal blocker in some cases because the research teams would be busy trying to find the ultimate identity of parent for conflict checks. As a result, sales teams were wasting times engaging customers they didn't need to, contracts were delayed as discovery took too long etc. Reputational/compliance risk is something we used to try to avoid.

Also commenting so I can come back.

[mfrye0]

Interesting. So in that case, who had the biggest pain point? The sales team from being held up, or the research time under pressure to deliver?

We actually haven't explored the big consulting firms yet. I know they are often contracted to do this sort of research for companies.

[mfrye0]

Since it's quiet here, figured I'd share what the API actually spits out. Here's MG Motor's ownership chain (this is just the Mermaid diagram field - we return a bunch of other stuff too):

  graph TD
    e2[SAIC MOTOR UK HOLDING CO., LTD.]-->|2005-02-15|e1[MG MOTOR UK LTD]
    e1[MG MOTOR UK LTD]-->|2018|e7[MG Sales Centre Limited]
    e4[SAIC Motor Corporation Limited]-->e2[SAIC MOTOR UK HOLDING CO., LTD.]
    e4[SAIC Motor Corporation Limited]-->e3[SAIC MOTOR INTERNATIONAL UK LTD]
    e5[Shanghai Automotive Industry Corporation Group]-->|62.69%|e4[SAIC Motor Corporation Limited]
    e6[Shanghai State-owned Assets Supervision and Administration Commission Shanghai SASAC]-->e5[Shanghai Automotive Industry Corporation Group]

You can copy/paste that into any Mermaid renderer to see it visually. Pretty wild how a British car brand ends up tracing back to Shanghai's government.

Happy to run lookups for other companies if anyone's curious what their ownership looks like!

[promiseofbeans]

How does it handle companies with huge numbers of subsidiaries, like Volkswagen?