Meet the first AI to say ''I don't know''. We think agent mass adoption is blocked by three things: 1) weak security, 2) unreliability, and 3) how hard agents are to set up. Our first product, Sage, is focused on reliability. It's a "decision model" - a safer, faster, and cheaper way for machines to choose, act, and escalate to a human when confidence is low. You give it content (up to 32K tokens) and a list of questions (Sort, Yes/No, Choice, Tags, Scale), and Sage answers in 200ms - 9x faster than a traditional LLM - always with a confidence score attached. So yes… it's humble enough to say "I don't know." You can also turn on "grounding" to automatically run a web search and enrich the context. Under the hood: we took an open-weights LLM and fused on a classifier through post-training. It's great for agentic workflows, agentic guardrails, data pipelines, content moderation, operations, and risk & fraud. Why does this matter? Today's LLMs are great for chatbots, research, and creativity - but automation needs something much faster, with structured outputs, that isn't overconfident and is ready to admit when the signal is too weak. Sage preview is live. Excited to see your feedback. Levanto Labs is out of stealth today, founded by @marco_derossi and @bigironchris. We are hiring, reach out! Check the links in the post below 😊
