Don't start by renting servers and burning money right away.

The most stable way to kick off an AI service is to first act as a "token broker," using big tech's quotas as a relay to validate demand at zero cost.
I’ve successfully run two relay projects, and the core logic is just three layers:
First stage: Light asset traffic hacking
Use personal developer quotas/free tiers to aggregate APIs, earning from "information gap + proxy operations." Customers never want you to train models yourself; they want stable calls + after-sales support.
Second stage: Reinvest after customer validation
Once daily request volume stabilizes, set up your own servers for a service pool. At this point, the marginal cost of renting computing power approaches zero, and profit margins expand directly.
The key barrier isn’t technology; it’s the sense of delivery.
Response speed, error retries, usage monitoring, transparent billing—these "invisible infrastructure" elements—are what make customers willing to pay continuously.
Implementation actions: 48-hour MVP validation checklist
1⃣ Register 2-3 major tech company developer accounts to get free quotas/test keys
2⃣ Use Cloudflare Workers or Vercel to set up a simple relay interface (there are open-source templates online, which can be up and running in an hour)
3⃣ Post in tech communities/social circles: “Stable large model API calls, first month at 9.9 yuan trial, automatic over-limit alerts + dedicated after-sales”
4⃣ Consider expanding only after reaching 10 paying users—don’t invest heavily on pseudo-demand first.
Let the market validate for you first, then let scale make you money.
Lightweight startup, rapid iteration—that’s the underlying rhythm for crossing over into AI services.
Friends working on AI relays or preparing to enter, share in the comments where your current bottleneck is? I’ll help you break it down.