How the AI Content Auditor Works

Four-Stage Verification Pipeline

Every document passes through a deterministic four-stage pipeline. No shortcuts. No sampling. Every claim in the document is extracted, verified, scored, and reported.

Decomposing AI output into
auditable assertions.

The auditor does not evaluate text as a block. It decomposes every AI-generated document into individual factual claims — each one a discrete unit that can be independently verified, sourced, and scored. This is the foundation of deterministic verification.

Claim Types

Decomposed Claim Structure

{
  "claim_id": "CLM-001",
  "text": "Revenue grew 23.4% year-over-year to $4.2B",
  "type": "numerical",
  "entities": ["revenue", "23.4%", "$4.2B"],
  "source_required": true,
  "confidence_threshold": 0.95
}

Each extracted claim carries metadata: type classification, entity list, source requirement flag, and the confidence threshold needed to pass verification.

Cross-reference methodology
and verdict classification.

Every extracted claim is matched against source documents, regulatory databases, and reference data. The engine does not guess — it either finds supporting evidence at a specific source location or it flags the absence. Each claim receives one of six deterministic verdicts.

Verification Verdicts

Verification Result Structure

{
  "claim_id": "CLM-001",
  "verdict": "MATERIAL_ERROR",
  "severity": "critical",
  "finding": "Revenue was $3.8B, not $4.2B. Growth was 19.2%, not 23.4%.",
  "source": "10-K Filing, FY2025, p.47",
  "confidence": 0.99
}

Verification results include the exact finding, source reference with page number, severity classification, and engine confidence. Every verdict is traceable and auditable.

0–100 accuracy score
with severity classification.

Every audited document receives a composite accuracy score on a 0–100 scale. The score is computed from verification verdicts, severity weights, claim density, and red flag counts. It is deterministic — the same document produces the same score every time.

Score Ranges

Red Flag Categories

Compliance Framework Coverage

The auditor maps verification findings to industry-specific regulatory frameworks. Each flagged claim is annotated with the compliance context it may violate, enabling risk and legal teams to prioritize corrections by regulatory exposure.

Integration Patterns

The AI Content Auditor exposes a RESTful API for programmatic access. Integrate audit capabilities directly into your content pipelines, CMS workflows, or CI/CD processes.

Sample Request

POST /api/v1/audit
Host: api.frisbyaiops.com
Authorization: Bearer sk_live_xxxxxxxxxxxxxxxx
Content-Type: application/json

{
  "document": "Revenue grew 23.4% year-over-year to $4.2B...",
  "source_urls": ["https://sec.gov/filing/10k-2025.pdf"],
  "modules": ["accuracy", "bias", "compliance", "tone"],
  "compliance_frameworks": ["SEC", "SOX"],
  "output_format": "json"
}

Sample Response

{
  "audit_id": "AUD-20260421-001",
  "score": 62,
  "rating": "HIGH_RISK",
  "claims_total": 47,
  "claims_verified": 31,
  "claims_flagged": 12,
  "red_flags": 4,
  "report_url": "https://api.frisbyaiops.com/reports/AUD-20260421-001",
  "processing_time_ms": 3420
}

Endpoint Reference

See the Auditor in Action.

Paste any AI-generated text and get a full accuracy audit with claim extraction, cross-reference verification, and scoring. No signup required for the live demo.