IntentParse: Turn natural language into structured, actionable intent

We built IntentParse because “understanding the user” is usually treated as a single opaque LLM step. But there’s an important difference between: * what the user explicitly said, * what can reasonably be inferred, * what constraints and preferences matter, * and what is still unknown. IntentParse turns that ambiguity into structured, validated intent that an application can inspect before deciding what happens next. The goal is not to let the model act with more confidence. It is to give developers a clearer boundary between **interpretation and execution**. That means applications can clarify missing information, route requests, apply policy, or trigger workflows without treating every model inference as a fact. IntentParse is available now, and I’d really like feedback from people building agents, support systems, marketplaces, and conversational interfaces. What would you want an intent layer like this to expose?