Midstream

Midstream solves a critical problem in AI: users pay upfront for output regardless of quality. Whether a research run drifts, code breaks, or an image is off-prompt, you've already paid full price. This wastes 30–70% of AI spending annually. Our solution: quality-gated streaming payments. The LLM generates output in 32-token chunks at $0.0005 each. Between chunks, the buyer's quality oracle (LLM, compiler, CLIP, etc.) assesses whether to continue paying. If quality drops below threshold, the buyer stops authorizing, the stream ends, and they pay only for the prefix that passed. We've built a working MVP on Circle Nanopayments + Arc testnet. Circle's batching achieves <1% overhead per chunk—impossible on Stripe ($0.30 minimum, 60,000% overhead) or Ethereum ($0.30 gas). Our demo shows: - Session 1: Full run, 31 chunks, $0.0155 - Session 2: Quality drop at chunk 13, killed, 60% saved - Session 3: Rapid drift at chunk 4, killed, 87% saved - Session 4: Compiler catches broken code at chunk 9, killed, 68% saved Total: 58 chunks paid, $0.0290 spent (vs. $0.0620 full run) = $0.0330 saved. We've verified 213 Circle Transfer UUIDs settled on Arc testnet via Circle Gateway batching. Every settlement is clickable on testnet.arcscan.app. The architecture is oracle-agnostic: works with any quality signal (text, code, image, video, schema validation, etc.). This is a platform, not a one-off.