Trust and compliance

AI Transparency

Legal documentation and governance details for Argusly customers and partners.

AI Transparency Statement

Argusly is designed for professional teams that want to use AI in content operations without losing editorial responsibility, review control, or provenance. This statement explains how we approach AI-assisted workflows and transparency.

Last updated: July 1, 2026

AI-assisted workflows

Argusly may use AI systems to support research, briefing, drafting, rewriting, translation, content improvement, answer blocks, image generation, and related workflow assistance.
AI functionality is intended to assist customer teams. It does not remove the need for human review, fact-checking, legal review where appropriate, or editorial responsibility before publication.
Customers choose how to configure workflows, approvals, connected sources, publishing destinations, and the degree of automation used in their workspace.

Human review and editorial responsibility

Argusly supports human-in-the-loop workflows through review states, approval flows, content revisions, publishing controls, and team roles.
Customer users remain responsible for reviewing AI-assisted output before relying on it or publishing it.
Enterprise workflows can use review, approval, and audit signals to show how content moved from draft to publication.

AI disclosure and provenance

Argusly is being built to record AI disclosure status per governed content asset, including whether content is human-created, AI-assisted, AI-generated, or AI-edited.
Provenance records may include generation events, review events, fact-check status, publishing actions, model history, prompt history, source trace, version history, and output hashes.
Machine-readable metadata and disclosure APIs are designed to help downstream systems recognize AI-assisted content and inspect provenance information.

Prompt and model handling

Prompts may include customer instructions, brand context, source material, draft content, and workflow configuration needed to perform the requested task.
Where available, Argusly records model provider, model name, run identifiers, prompt hashes, output hashes, and generation settings for audit and troubleshooting purposes.
Prompt history may be summarized or redacted where sensitive information should not be exposed broadly to all users or external systems.

Sources and fact-checking

Argusly may store source references, retrieval status, source titles, URLs, timestamps, and related metadata when sources are used in research or generation workflows.
Source traceability helps customer teams inspect what informed an output, but it does not guarantee factual correctness by itself.
Fact-check status and reviewer notes can be used to document whether claims are unchecked, supported, partially supported, conflicting, or require human review.

Limits of AI output

AI output may be incomplete, inaccurate, outdated, biased, or unsuitable for a particular legal, medical, financial, regulatory, or brand-sensitive use case.
Argusly does not guarantee that AI-assisted output is factually correct, legally correct, free from third-party rights, or appropriate for publication without review.
Customers should apply their own review, approval, source verification, and compliance process before publication or external use.

Customer controls

Configure workflows and approval gates
Review and edit generated content before publication
Use source trace, model history, and audit reports where available

Transparency records

AI badges and disclosure status
Provenance timelines and workflow events
Downloadable audit reports and machine-readable metadata

Questions about legal or compliance?

Reach out to our team for questions about data processing, security practices, or contractual terms.