For Researchers

Technical documentation and validation data

This section provides the full technical detail behind Veridi’s methodology and testing. If you’re evaluating the system’s rigor, designing similar systems, or looking for something to break, start here.

What’s available

Validation Report: Complete documentation of the three-phase validation process: 97 claims across 8 domains, 9 verdict categories, 26 adversarial scenarios (24 in the original validation suite plus ADV-025 and ADV-026 added in v2.6 and v2.7 for self-reference coverage), 4 non-English languages, and genuinely contested ground truth. Includes per-claim results, pass criteria, and a frank discussion of limitations.

Adversarial Testing: Veridi’s 12 gaming vectors, how each is detected, and how the methodology performed against 26 adversarial claims (12 single-vector, 14 multi-vector). Includes 4 claims based on documented real-world disinformation patterns and 2 self-reference claims (ADV-025 methodology, ADV-026 substrate; v2.6 and v2.7 respectively). (Pragma’s distinct gaming-vector count is 14, corrected from 11 in the v1.2 audit; Praxis adds 6 native vectors plus 8 inherited from Pragma for 14 combined cross-references. The three taxonomies are related but not identical; see each product’s gaming-countermeasures documentation for the precise vector list.)

Confidence Calibration: The framework for assigning confidence ratings: tier-based structural ceilings, field reliability coefficients with sourcing honesty labels, and the interaction rules that prevent absurd multiplicative results.

Gaming Countermeasures: Detailed documentation of all 12 disinformation detection procedures, including detection difficulty ratings, impact severity, the relationship to the Institutional Reliability Index, and the v2.7 substrate self-reference vector with its 75% confidence ceiling.

Key numbers

Known limitations

These are described in detail in the validation report and the known limitations page. The short version:

• Near-perfect results warrant scrutiny. The test suite was designed by the same people who built the methodology.
• Validation was conducted by the methodology’s own implementation (AI following the procedures), not by human volunteers; thus, results are not a pure reflection of the defined methodology alone.
• Most adversarial claims were constructed for testing, though 4 were based on real-world disinformation patterns.
• The methodology has not yet been tested at scale with human users.
• Brier score calibration data has not yet accumulated enough data points for statistical significance.

We welcome external validation, particularly claims designed to produce incorrect results. To request the full methodology files or submit test claims, use our contact form.