360 experiments. 6 verification layers. Zero tolerance for unverifiable claims.
Evidtrace is an independent AI vendor credibility intelligence platform. Every claim made by AI vendors is extracted, verified against independent evidence, and scored. The methodology behind the engine was developed through 360 structured experiments across real-world news and vendor claims.
AI vendors routinely make claims about model capabilities — benchmark scores, reasoning ability, safety metrics — that cannot be independently verified. Press releases are treated as evidence. Self-reported benchmarks are cited as fact.
Traditional fact-checking was built for politics and health. AI vendor claims require a fundamentally different approach: one that understands benchmarks, technical specifications, and the difference between self-reported and independently verified evidence.
Every claim passes through six independent verification layers before receiving a final credibility verdict. Each layer was calibrated through dozens of structured experiments.
Every rule in the verification engine traces back to a specific experiment. Five research phases, from foundational calibration to live engine testing.
Six experiments that shaped the verification engine's core logic.
of stories had wire-rewrite duplicates. Outlets rewriting AP/Reuters copy appeared as independent reporting — inflating apparent source diversity without adding evidential weight.
of headline rounding was in the dramatic direction. Numbers were consistently rounded to make stories appear more significant, distorting the claims being verified.
correlation between emotional framing and spread speed. High-emotion stories travelled faster but carried weaker evidence — requiring elevated evidentiary thresholds.
of corrections went uncarried by downstream outlets. Once a claim enters the information ecosystem, corrections rarely propagate — the original claim persists.
of claims were anonymously sourced. The engine applies a systematic 15% credibility discount to anonymous claims — calibrated against cases where sources were later identified.
of cases showed narrative lock-in — once a dominant interpretation formed, contradictory evidence was filtered out or underweighted by subsequent coverage.
Programmatic access to Evidtrace intelligence. All endpoints return JSON with full provenance metadata.
Query assessed articles with filtering by date, category, provider, and verdict. Returns full article metadata with linked claim IDs.
Search verified claims by keyword, provider, or verdict status. Each claim includes its full verification trail and confidence score.
Provider credibility profiles with historical scores, claim counts, category presence, and trend data across editions.
Edition metadata including assessment counts, date range, methodology version, and aggregate statistics.
How Evidtrace supports deployer obligations under Regulation (EU) 2024/1689
Evidtrace is supplementary vendor intelligence designed to inform procurement decisions. It does not satisfy deployer obligations under Article 26 on its own and should be used alongside task-specific validation, operational controls, and legal review.
The EU AI Act imposes specific obligations on deployers of high-risk AI systems. Article 26 requires deployers to:
Certain deployers — notably public authorities and organisations providing public services — must conduct fundamental rights impact assessments prior to first use of high-risk AI systems.
Source: EU AI Act — Article 26, Regulation (EU) 2024/1689
When errors are identified in Evidtrace assessments — whether by internal review, external scrutiny, or vendor response — they are corrected in the next edition. A changelog is maintained for each edition documenting material corrections, additions, and removals.
Vendors may submit corrections, context, or rebuttals via hello@evidtrace.com. Vendor responses are reviewed and, where appropriate, noted in subsequent assessments.
Previous editions remain available for audit trail purposes. Correction history is part of the assessment record.