LLM Output Stream Processor

A parsing engine that converts any input format (Markdown, HTML, XML) into semantic event streams for real-time processing. Ideal for LLM inference pipelines needing structured, transformable output.

LLM streaming output is increasingly the default UX pattern as inference providers like OpenAI, Anthropic, and open-source runtimes all expose token-by-token streams, but the tooling for parsing and acting on that stream in real time is still largely hand-rolled by each team. No clear incumbent owns this space — Vercel's AI SDK touches adjacent ground but is framework-coupled and React-first, leaving backend and polyglot pipelines underserved. The $2k–8k/mo revenue band is plausible only as a hosted or managed service with usage-based pricing; a pure library almost certainly stays open-source and earns nothing. The core risk is that this remains a thin utility layer that LLM SDK maintainers absorb as a minor feature release, collapsing the wedge before any meaningful customer base forms.