9 use cases for Jev (System 1 Model): - Re-ranking: Score and reorder retrieved results by relevance. - Tool pruning: Drop unused tools during context compaction. - Model routing: Route tasks to small, medium, or large LLMs. - Query routing: Decide between SQL, Vector DB, or Graph DB. - Cache admission: Filter which responses are worth caching. - Cache TTL prediction: Estimate how long cached results stay valid. - RAG retrieval control: Gate irrelevant retrieved documents. - Human escalation: Know when to hand off from AI to a human. - Action selection: Score and pick the best next agent action.

9 use cases for Jev (System 1 Model) in Real-Time Voice AI Agent: - Turn detection: Decide whether the user has finished speaking. - Barge-in detection: Detect whether incoming speech is a real interruption or just a backchannel. - Intent classification: Identify the user's intent from the conversation. - Agent routing: Route the conversation to the right specialized agent. - Human escalation: Decide when the conversation should be handed off to a human. - Confirmation detection: Decide whether a sensitive or ambiguous action needs confirmation. - Tool selection: Decide which tool or API should be invoked next. - Response verification: Check whether an LLM response is safe and appropriate to speak. - Conversation state: Determine the next state or action in a voice conversation.