CONSEQUENCE FIRST
Verify what could actually hurt.
Not every sentence deserves equal effort. ProofTTL identifies atomic factual claims and prioritizes the ones most likely to create customer, compliance, financial, or reputational damage if wrong.
Fact AuditStart audit
AI FACT CHECKER / SOURCE-BACKED VERIFICATION
Find the expensive wrong answer before your customer does.
Send ProofTTL 10–25 real AI outputs or consequential claims. We decompose the factual assertions, rank them by damage-if-wrong, deeply verify the highest-risk findings against authoritative evidence, run a contradiction pass, and prepare the result for human approval.
Fixed scope: $1,500. Up to 25 outputs or claims reviewed, with deep verification of the highest-risk findings. Human approval is required before customer-facing publication.
FOR / AGAINST / CONTRADICTION PASS
See the evidence chain, not a confidence vibe.
Important findings are checked against inspectable evidence on both sides. Verdicts remain SUPPORTED, CONTRADICTED, or UNKNOWN when the public record does not justify stronger certainty.
THE FACT AUDIT
One deliverable built for decisions that matter.
$1,500 fixed scope
Submit 10–25 real outputs or claims. Scope is confirmed before payment so the engagement is clear before money moves.
Evidence-backed findings
Receive ranked findings, readable reasoning, authoritative source evidence, explicit verdicts, and proof artifacts suitable for review.
Seven-day watch
Important findings enter seven days of monitoring with a final re-read so a changing source does not silently invalidate the audit.
COMMON USE CASES
AI research and reports
Verify market sizes, dates, company facts, policy claims, statistics, and cited assertions before a report leaves your hands.
Sales and product claims
Check competitor, pricing, feature, certification, integration, customer-count, and performance claims before publication.
Decision-critical answers
Pressure-test claims that could change a purchase, launch, client recommendation, compliance decision, or internal strategy.
WHY PROOFTTL
Verification that can say “we don’t know.”
ProofTTL does not pretend to inspect a model’s internal truthfulness. It asks a narrower, auditable question: what does the available evidence support about this exact claim? When evidence is insufficient or execution is incomplete, certainty is withheld instead of invented.