Most knowledge systems store facts. Veritas stores how well you know them .

I built Veritas because AI agents have an epistemic blind spot: they act on beliefs they can't evaluate. "The API is reliable" — based on what? One observation from 2022? Twenty independent tests from last month? A single assumption that everything else depends on?

Without structure, agents overclaim certainty or collapse into paralysis. Veritas gives beliefs a shape.

Confidence is a vector, not a number

Every claim in Veritas carries a ConfidenceVector with four components:

Field Meaning

value Current best estimate (0–1), with temporal decay applied

fragility How much confidence drops if the best source is removed

staleness_penalty How much evidence aging has already cost

source_diversity How independent your sources are

Sources are combined using noisy-OR pooling — the same model used in fault trees — so independent confirmation genuinely compounds, but correlated sources don't double-count.

from veritas import VeritasDB…