Automatically analyzes and optimizes AI prompts by calculating clarity scores, detecting risks, asking clarifying questions, and adding domain-specific requirements to improve AI interaction quality.
Enables AI assistants to identify and judge unexplained terms in prose documents by providing differential linting, term context, and ledger management.
Classifies text into structured semantic units with authority, risk, and attention scores. Enables deterministic preprocessing for AI agents to filter and route content without using an LLM.
Enables natural language queries to be converted into policy-verified SQL, vector search, and knowledge graph plans, with evidence-backed answers and an audit log.
Enables AI agents to access crypto market signals including regime, sentiment, price, risk, and text tools like summarization and fact-checking, backed by a live production-grade classifier.