Who Actually Makes Money with OpenClaw? A Data‑Driven Look at 168 Projects

Data Source and Goal

The author extracted 168 OpenClaw‑related projects from the TrustMRR site to identify which participants are generating revenue and how the money is distributed.

Overall Revenue Landscape

The ecosystem has generated a cumulative $3.18 million in historical revenue and a current monthly recurring revenue (MRR) of $148 k . Out of the 168 projects, 97 projects (57.7%) have reported any income, while 22 projects are listed for sale as founders consider exiting.

Income Distribution

The revenue tiers are starkly uneven:

$0 – 71 projects (42%)

$1–$500 – ≈40 projects (24%)

$500–$5,000 – ≈30 projects (18%)

$5,000–$50,000 – ≈20 projects (12%)

Above $50,000 – ≈10 projects (4%)

More than sixty percent of projects earn less than $500.

Top Earners Capture Most Revenue

Three projects dominate the income pool, accounting for roughly 90% of total revenue :

Roofclaw (vertical roofing SaaS) – $1.81 M (57%)

Donely (hosted SaaS) – $750 k (24%)

AI Money Group (education/consulting) – $290 k (9%)

The remaining 165 projects together contribute only $330 k (10%).

Business Model Insights

The analysis shows that the majority of participants are not using OpenClaw to improve enterprise efficiency. Instead, they monetize “peripherals” such as:

Installation services and cloud deployment

Training and tutorial packages

Courses on “how to make money with AI”

These activities address users’ learning costs and technical anxiety rather than delivering core operational value.

Project Type Breakdown

Hosted SaaS (one‑click deployment) – 82% (≈138 projects)

Upper‑layer applications (specific functions) – 8% (≈14 projects)

Service / education consulting – 6% (≈10 projects)

Development tools / marketplaces / others – 4% (≈6 projects)

Token‑Cost Pitfall

A Shenzhen programmer received a token bill of ¥12,000 after three days of OpenClaw usage, illustrating the risk of uncontrolled API costs.

Who Is Actually Earning?

The money flows through three layers:

Ordinary users / independent developers : sell hosted services, tutorials, and installation. Collectively they generated $3.18 M, but 42% earned nothing and only 2‑3 projects made substantial profit.

Large model providers (e.g., Kimi, MiniMax, Alibaba Cloud) : capture billions of tokens in weekly usage, translating into multi‑billion‑dollar revenues.

Cloud and compute providers (AWS, Alibaba Cloud, Nvidia) : benefit from the underlying GPU demand, representing a trillion‑dollar market.

The diagram of cash flow shows users paying API fees, model companies receiving token revenue, and cloud providers earning from the compute layer.

Conclusion

The OpenClaw ecosystem demonstrates a classic “money‑up‑the‑chain” pattern: a few top projects reap most of the earnings, most participants rely on ancillary services, and the largest financial gains accrue to model and cloud providers rather than to the tool’s direct efficiency gains.