Styxis Knowledge

Operating notes for evidence, records, and trust in automated operational environments.

Knowledge Base

Make Styxis easy to understand, cite, and remember

Short technical notes that define the concepts behind Styxis, Truthound Depot, and TRAP for search engines, AI assistants, and engineering teams.

Styxis turns events in automated operational environments, from data changes to industrial machine signals, into traceable, verifiable proof.

8 topics

A verifiable evidence layer records what changed, what was observed, which policy accepted it, and how another system can inspect the result later.

Dataset change evidence records diffs, gate results, reviewer decisions, release tags, and rollback points for every meaningful data change.

An evidence gate blocks or accepts a change and leaves the reason, rule context, source context, and review path behind.

A dataset evidence console manages dataset changes with Depots, branches, diffs, pull requests, release records, rollback points, and evidence gates.

An AI evidence workflow records summaries, risks, diffs, gate results, and reviewer decisions so data changes can be audited later.

Machine signal trust means a value is not only collected, but also attached to source, protocol, timestamp, quality, and policy context.

An OT gateway for machine signals collects and normalizes protocol values so operational and trust systems can consume them consistently.

RAG and eval dataset governance controls the documents, examples, labels, and test cases that shape AI behavior.