> For the complete documentation index, see [llms.txt](https://apidex.gitbook.io/apidex-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://apidex.gitbook.io/apidex-docs/what-apidex-solves/the-problem-framework.md).
# The Problem Framework
We categorize the structural deficiencies of the current LLM market into three layers:
* ### **Pricing Layer**
Monopolistic Price-Setting. AI providers hold absolute pricing power. Users can only "take it or leave it." There is no bidding mechanism, no market depth, no price transparency. Research from Epoch AI shows that inference price declines vary by up to 100x across different task types \[7], yet users cannot benefit from this imbalance because no arbitrage mechanism exists.
* ### **Liquidity Layer**
Non-Transferable Compute. Current API credits are "use-it-or-lose-it" consumables. Enterprises that procure large volumes of compute cannot transfer excess capacity during demand troughs. Individual developers cannot temporarily acquire additional compute from the market during demand spikes. This liquidity vacuum produces massive resource misallocation.
* ### Risk Layer
No Hedging. For enterprises whos**e c**ore cost structure depends on AI inference (SaaS products, AI agent companies, content generation platforms), compute cost volatility directly impacts margins. Yet they possess no financial instruments to lock in future compute costs.
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