When LLMs Disagree About the Same Company

Different LLMs often provide different descriptions of the same company: founding year varies, product scope shifts, and even company status can change depending on the model. This case examines why divergence happens when no canonical source exists. Each model reconciles fragmented data differently, especially when sources conflict or lack timestamps. Using a structured, verified company profile as a reference point reduces variance across models. The case shows how factual convergence improves once LLMs retrieve data from a single, authoritative layer instead of probabilistic inference.