Sage2 Launches: AI Updates Judgments Mid-Conversation, Boasts Fastest Response Time of 50 Milliseconds

Insight from Beating AI: U.S. AI startup Levanto Labs has launched Sage2, a model that combines information extraction with real-time decision-making. It can automatically extract details like amounts, dates, and user needs from chats, and continuously adjust its judgments based on new content. For example, Sage2 can monitor user sentiment for web-based AI customer service tools. If a user initially asks for a refund but grows increasingly frustrated, Sage2 will update its assessment accordingly. When the user’s dissatisfaction hits a pre-set threshold, the system automatically transfers the interaction to a human agent, no need for the user to request it explicitly. According to the company, Sage2 takes around 150 milliseconds to extract information from short text, with a judgment update as fast as 50 milliseconds. The system retains conversation context and reuses computational caches, eliminating the need to resubmit full chat logs each time. It is primarily targeted at use cases like customer service, business automation, and AI agents, making it suitable for handling large volumes of repetitive judgment tasks. Compared to calling general-purpose large language models, this specialized decision model is expected to reduce latency and costs. In the company’s in-house evaluation, Sage2 scored 77.8 in information extraction accuracy, slightly outperforming Cloudflare’s data extraction model Clairic, which scored 75.3.