Process
1. Clarify first: Mono checks whether your question is clear enough for research. If not, it asks a few focused follow-up questions before searching.
2. Search the web: It generates targeted Google-style queries and collects diverse sources from multiple domains.
3. Extract usable evidence: Each page is downloaded and cleaned into readable text so models can reason over content.
4. Run multiple model analysts: Gemini, Claude, and OpenAI models independently analyze the research target against the source material.
5. Compare viewpoints: The system highlights where models agree, disagree, and where each one may have blind spots.
6. Synthesize one final answer: A final summarizer produces a single clear response, grounded in the multi-model outputs.
Web search adds real-world grounding, so models work from retrieved source content. Cross-model validation catches weak claims, one model’s miss is often another model’s strength.