Which startups have raised the most funding in the embodied AI market?

The embodied AI market is moving fast, with funding flowing into humanoid robots, robot foundation models, warehouse automation, autonomy software, and spatial intelligence platforms.

We update this list every month, so the ranking can reflect new rounds, exits, and changes in public funding data.

This page ranks embodied AI startups by cumulative funding raised, using the data available from public and reliable sources.

A few word about our methodology

As you can see, we built a database that ranks startups in the embodied AI market based on their total cumulative fundraising. To create this ranking, we reviewed many sources and cross-checked information across multiple places.

Whenever possible, we prioritized official company communications, since official announcements are usually the most reliable source for funding amounts. When those were not available, we relied on reputable industry sources such as TechCrunch, Crunchbase, Financial Times or Forbes (to name a few).

We excluded random blogs, unverified websites, and any sources that could not be validated.

When funding rounds were announced in other currencies such as euros, Swiss francs, Singapore dollars, Australian dollars, or rupees, we converted them into approximate USD equivalents for consistency.

Sometimes different sources report slightly different numbers, or the exact round size is not fully disclosed. In those cases, we flag the uncertainty and assign a confidence label to each startup, visible in the last column.

Here is what they mean.

Full confidence: The company’s equity fundraising history can be reconstructed completely from public sources. The rounds, dates, amounts, and key investors are clearly identified, with no meaningful gaps.

Strong confidence: The fundraising history is largely complete and reliable. There may be a small missing detail, such as incomplete investor information or a minor round with limited data, but the overall record is clear.

Partial confidence: The main fundraising rounds can be identified, but the record is incomplete or somewhat mixed. Some rounds may be missing or certain funding events may be difficult to separate clearly.

Low confidence: Public information is too limited, inconsistent, or ambiguous to reliably reconstruct the company’s equity fundraising history.

When the confidence level is too low, we take a conservative approach and exclude the company from the ranking. We don’t want to include data that cannot be reliably verified.

In a world where LLMs hallucinate and unreliable information is everywhere, our goal is simple: provide data you can trust.

If you want the full detail on a specific calculation, feel free to contact us and we will gladly explain.

Finally, know that we update the dataset once per month, so come back here if you need fresh information.

Who is the author of this content?

NEW MARKET PITCH TEAM

We track new markets so founders and investors can move faster

We build living “market pitch” documents for emerging markets: from AI to synthetic biology and new proteins. Instead of digging through outdated PDFs, random blog posts, and hallucinated LLM answers, our clients get a clean, visual, always-updated view of what’s really happening. We map the key players, deals, regulations, metrics and signals that matter so you can decide faster whether a market is worth your time. Want to know more? Check out our about page. You can also follow us on Instagram or on Facebook.