Insights on AI unit economics

Per-customer margins, pricing strategies, MCP finance workflows, and the operational realities of running LLMs in production.

The AI Gross Margin Crisis Nobody Talks About
The average AI-native B2B company runs 52 percent gross margin. Classic SaaS runs 80. The gap is inference cost, and it is getting wider.

Your Inference Bill Is Not R&D. It Is COGS.
LLM API spend is classified under engineering at most AI companies. That misclassification hides per-customer margins, distorts pricing, and delays the conversation your board will have.

Voice AI's Hidden Margin Problem
Voice AI companies stack STT, LLM, and TTS costs per call. At scale, the per-minute COGS compresses margins faster than any other AI modality. Here is the math.

AI Gateways Cannot Price Without Margin Attribution
AI gateway and routing companies resell tokens. Their gross margin is the spread between what they pay vendors and what they charge customers. Without per-customer cost tracking, that spread is invisible.

Agentic Workflows Burn 100x More Tokens. Your Pricing Does Not Know.
Multi-agent reasoning tasks use orders of magnitude more tokens than simple completions. If your pricing has not adjusted, your margin is shrinking with every new feature you ship.