Last month we asked four AI models whether a specific drug interaction was safe. Two said yes. One said probably. One said no. All four were confident. Only one was right. That's the problem SIBYL was built to solve. Instead of trusting a single model, SIBYL runs your question through multiple AI models independently. They analyze, disagree, and challenge each other — then SIBYL produces a final arbitrated answer with a real confidence score, flagged disagreements, and a Decision Receipt showing exactly how the conclusion was reached. Think of it like a boardroom of AI models that debate before giving you a final answer. And if certainty is too low, SIBYL will tell you it doesn't know rather than guess. Some early ways people are using it: • Researchers & analysts – sanity-checking complex questions • Developers – verifying LLM outputs before shipping them in apps • Founders & operators – stress-testing high-stakes decisions We're still early and building in the open, so we'd genuinely love feedback from this community. The question we keep debating internally: When should AI refuse to answer instead of guessing? We'd love to hear where you'd draw that line. Happy to answer anything about how the arbitration works or where we're taking SIBYL next..

SIBYL

Verified Intelligence

Verified Intelligence