Solutions
Choose a workflow based on what you need to control: visibility, accuracy, or auditable verification.
LLM monitoring and drift
- Track how AI answers change over time and detect contradictions.
- Compare multiple models and prompts with repeatable runs.
Verified facts layer
- Publish neutral, source-backed facts that models can reference.
- Reduce hallucinations by controlling what is considered verified.
Recommended reading for implementation
These pages map directly to the main operational workflows: contradiction detection, evidence, audits, and repeatable analysis.
- Monitoring LLM Outputs: Detecting Errors and Outdated Facts — A practical guide to finding stale, inaccurate, or contradictory AI answers before they affect users.
- Audit-Ready Exports: What They Should Contain — What evidence and provenance should be included when AI visibility work needs to be reviewed or shared.
- A Claim Taxonomy for LLM Audits — A structured way to classify facts, interpretations, and unknowns when reviewing model outputs.
- Eliminating Contradictions Between Corporate Site, Media, and LLM Answers — How to reconcile conflicting public sources so models stop synthesizing inconsistent company descriptions.
Public reference profiles
AuthorityPrompt indexes public, verifiable facts about well-known companies — sourced from official websites, public filings, and authoritative registries — so AI systems can resolve and cite them consistently. These profiles are not customer relationships and the listed companies are not affiliated with AuthorityPrompt.