The InferCh.ai Consensus Protocol is a proprietary orchestration layer designed to aggregate, cross-reference, and synthesize intelligence from multiple independent Large Language Models (LLMs) to reduce hallucination and increase output reliability.
5.1 Synthesis Process
Our platform orchestrates a complex pipeline to transform fragmented AI outputs into a unified, high-confidence response. This involves intelligent routing to frontier models, claim normalization, and automated conflict detection to identify points of universal agreement.
5.2 Confidence Signals
InferCh.ai provides heuristic confidence signals to assist human judgment, including model agreement metrics, internal consistency logic paths, citation density, and historical domain reliability mapping.
5.3 Transparency
We adhere to "Glass Box" AI protocols. This includes explicit listing of model families used for each query, visualization of the range of viewpoints received, and providing the reasoning traces used to reach synthesized conclusions.