Published News

We’ve decided to keep Claude Pro and Perplexity Pro alongside Suprmind to leverage their unique strengths in orchestration versus aggregation

Model disagreement helps spot tricky inputs by measuring ensemble variance or entropy. When models strongly disagree, it signals uncertainty or risk

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DCI helps you track the full history behind your data decisions so you can verify accuracy and spot risks. It creates a clear audit trail, making it easier to trust complex insights without digging through endless files

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After testing Claude Pro, Perplexity Pro, and Suprmind, we’re canceling Claude and Perplexity to focus on Suprmind’s orchestration approach

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Model disagreement helps spot risky inputs by measuring uncertainty like ensemble variance or prediction margin. When models don’t agree, it flags cases that need extra attention

We’re canceling Claude Pro and Perplexity Pro to streamline AI workflows under Suprmind. Unlike simple aggregation, Suprmind orchestrates multi-model insights sequentially, compounding strengths while leveraging disagreement as a feature to spot errors

When models disagree, it often signals uncertain or risky inputs. Measuring disagreement using metrics like ensemble variance or margin helps spot those tricky cases