4 Market
Customers are developers, businesses, and service providers building agent services. The market is actual resource spending, beginning in Chinese-speaking markets in China and Southeast Asia.
Praxis’s paying customers are developers, businesses, and service providers using agents in their operations, buying the resources needed to run those services.
Three customer groups
The first group is creators and independent developers. They can use and build specialized agents in Praxis App, turning experience into services for customers; the App should balance professional depth and ease of use, attracting users through work rather than paid advertising.
The second group is small and medium-sized teams and businesses, such as a shop adding support to its website. They can build and run agents on Praxis or keep their own execution environment and use only resource services.
The third group is companies offering agent services to other businesses or customers. Praxis sits upstream, providing execution capabilities and resources; as they serve their customers better, platform usage has room to grow.
All three groups pay for actual usage rather than software licenses. Even a subscription buys resource usage; Personal Agents help these customers produce and operate services, rather than creating a separate mass-market personal assistant business.
What they buy
We focus on model inference, sandboxes, search, runtime compute, and related service fees. Inference is a model processing input and generating output, something that happens repeatedly as an agent works.
Pure software licensing is outside our chosen revenue model. We believe that as features become easier to copy, more value will lie in ongoing services and resources.
Size and adoption
Industry reports help show trends, but their different definitions cannot be added together or treated as revenue Praxis can capture. The table separates market estimates, usage, and survey findings, and identifies evidence still to be supplied.
| Observation | Existing figures and sources | What it indicates |
|---|---|---|
| Agent market | About USD 7.6 billion in 2025; about USD 50 billion in 2030 at roughly 46% annual growth. See Grand View Research and its 2025 forecast announcement | An industry forecast, not a market share we have secured |
| Enterprise generative AI spending | USD 37 billion in 2025, 3.2 times the previous year, in the Menlo Ventures report | Enterprises pay for AI; the report’s scope is not the same as our resource revenue |
| Model usage | Existing figures attributed to IDC are 1,944 trillion tokens in China’s public cloud in 2025, about 16 times year-on-year, with a further roughly 20-fold increase forecast for 2026; the report date and original link remain to be supplied. Google reported in May 2026 that monthly processing had grown about sevenfold year-on-year | Resource consumption and revenue need not grow at the same rate |
| Developers | About 48 million globally and 12 million in China, from SlashData 2025 and CSDN September 2025; original links remain to be supplied. The 23% weekly agent-use figure attributed to the Stack Overflow 2025 survey still needs its statistical definition | A broad potential base of integrators, not a paying-customer count |
| Agent building | Existing figures attributed to Coze are 500,000 developers and 200 million agents on Coze in 2025; original sources and definitions remain to be supplied | Evidence of building activity, not a count of active services |
| Creators | The existing figure attributed to Goldman Sachs is about 50 million creators; the date and original link remain to be supplied. In Adobe’s 2025 survey, 86% of respondents used creative generative AI | Creators use AI, but that does not mean all creators need this platform |
The number of customers willing to buy agent resource services in our target regions, their budgets, and the resulting addressable spending remain to be supplied.
Start in familiar markets
We start in Chinese-speaking markets in China and Southeast Asia. These markets are close to competitively priced Chinese model supply, have existing resource demand, and are familiar to the team; entering Europe or North America directly would add market-learning and operating costs.
Existing figures supporting this supply argument show Chinese models’ share of OpenRouter tokens rising from below 2% to 46%, attributed to June 2026. The historical snapshot and measurement basis remain to be supplied; a live ranking cannot substitute for historical evidence.
This is not a claim that one market is naturally easier. We first test and improve our methods in a familiar market, then take reusable systems elsewhere; systems should be broadly applicable but still need to fit local business conditions.
Grow with customers’ businesses
Companies providing agent services need execution and resources. We sit upstream and grow with their businesses rather than create all end-customer demand ourselves.
Resource access also has commercial value: Stripe announced an agreement to acquire OpenRouter, with TechCrunch reporting a price above USD 7 billion. An agreement is not a completed transaction; the amount is a media report, not a basis for valuing Praxis.
Products must turn the opportunity into something customers can use. The next chapter separates our existing progress from work still underway.
3 Why now
Models can do useful work, businesses need ongoing service, and AI lowers platform development costs. We start with smaller businesses that have not committed to a platform.
5 Product & traction
The model service and Praxis App have usage and revenue records. September 2026 figures are historical; current capabilities, work in progress, and year-end goals are separate.