fact-check

You can verify conversational claims by identifying verifiable statements and validating them against code or documentation. The workflow triages claims, uses fresh-context sub-agents for validation, and generates a report labeling findings as Supported, Contradicted, or Unverifiable.

Evidence-driven verification audits code by extracting verifiable claims through triage, then using fresh-context sub-agents to validate them against sources. It generates an audit-ready report with concrete evidence citations for compliance reviews.

Yes, automated claim verification works with external sources and knowledge bases by using fresh-context sub-agents to validate extracted claims. It checks conversational statements against code, documentation, and external sources, providing evidence-based verdicts.

Two-stage claim verification handles unverifiable statements by assigning them a fixed Unverifiable category in the final report. After triage and fresh-context validation, claims lacking concrete evidence are explicitly labeled Unverifiable alongside Supported or Contradicted findings.

Yes, you can generate a compliance report for contradicted claims by running the verification workflow on your codebase. The audit-ready report summarizes findings, labeling contradicted claims with concrete evidence and source citations for review.

Use automated fact-checking for conversation verification when you need to reduce misstatements in chats, codebases, or knowledge bases. It provides evidence-based verdicts with concrete source citations, making it suitable for audit-ready compliance reviews.