Most AI assistants are asked to be truthful. Viavitna is built so that untruthful output has no path to the user. Here is the pipeline, honestly explained.
The drafting model in Viavitna is never the final authority on what gets said. After it drafts an answer, structural checks and a separate fail-closed semantic pass re-evaluate whether each claim is supported and actually answers the question:
If semantic verification is unavailable, malformed, or incomplete, no generated claim is accepted. Viavitna returns source text or abstains, and its decision receipt binds the evidence and validation state.
Answers come from the extractive floor: a relevant passage from your content, quoted and cited, or a clear abstention. It is a safe degradation, not a generated guess.
Viavitna abstains, in plain language. An off-topic question that accidentally matches a stray word is caught by a coverage check and politely declined.
A recall-rescue pass rewrites the search using your pages' own vocabulary and semantic routing — and a retry is accepted only if it produces a fully verified answer.
Content is treated as untrusted reference text, never as instructions — and even an obeyed injection couldn't survive verification, because its output would be uncited.
Generation runs at temperature 0 with a fixed seed and schema-constrained decoding — the same question against the same content yields the same answer, so behavior is testable and reviewable rather than a slot machine. Models are open-weight (Apache-2.0) and run on hardware you or we control; there is no third-party AI API anywhere in the loop.
Your content is versioned: uploads create a draft you can interrogate in the review console, and nothing reaches visitors until you publish it. Re-uploading updates the draft; publishing is always a deliberate human act.
Viavitna