A system routes a query to a plurality of generative language models and aggregates their outputs to produce a final answer. A triage model determines a task type and a plurality of specialties from the query and maps individual specialties to corresponding generative language models, at least one of which is a locally hosted model that processes the query within an infrastructure that retains the query. Individual generative language models return a probability distribution over a set of candidate answers. A combined probability distribution is computed as a weighted sum, in logarithmic space, of the probability distributions under expert weights that are positive and sum to one, and is normalized. A final probability distribution is determined from the normalized probability distribution. A consensus model emits the final answer based on the final probability distribution and on a rationale received from individual generative language models.