Multi-Model Synthesis

Combine outputs from multiple AI models into a verified, comprehensive assessment by cross-referencing claims against the actual codebase.

Core Principle

Models hallucinate and contradict each other. The source code is the source of truth. Every significant claim must be verified before inclusion in the final assessment.

Process

1. Extract Claims

Parse each model's output and extract discrete claims:

• Factual assertions about the code ("function X does Y", "there's no error handling in Z")
• Recommendations ("should add validation", "refactor this pattern")
• Identified issues ("bug in line N", "security vulnerability")

Tag each claim with its source model.