What is per-customer cost attribution without a proxy?

It's logging LLM token usage and costs directly from API responses, tied to user IDs via async jobs—no routing through third-party services.

How do I implement AI cost tracking without latency?

Call providers directly with SDKs, extract usage from responses, queue background jobs to calculate and store costs per user.

Why avoid proxies for OpenAI cost tracking?

Proxies add 50-200ms latency, create failure points, and expose sensitive data to vendors—async logging fixes all that.

🤖 AI Dev Tools

No More Proxy Hell: Attribute AI Costs Per Customer, Lightning Fast

Everyone's been funneled into proxy hell for AI cost tracking. But what if you could pin exact costs to each customer—without the slowdowns or single points of failure?

theAIcatchup Apr 08, 2026 4 min read

Diagram showing direct LLM API flow with async cost logging, no proxy

⚡ Key Takeaways

Ditch proxies for direct LLM calls and async logging—zero latency, full control. 𝕏
Per-customer attribution reveals unit economics, spotting money-losing power users. 𝕏
This mirrors AWS tagging's rise; expect it to become AI dev standard. 𝕏

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theAIcatchup

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#AI cost tracking #LLM attribution #OpenAI billing #SaaS unit economics #multi-tenant SaaS #per-customer attribution #proxy-free logging

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Originally reported by dev.to

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