How CramKit verifies every question
AI can write a plausible practice question with the wrong answer. Most prep platforms never check. CramKit puts every question through a five-stage pipeline before it can appear in your exam — so you are never practicing on a wrong-keyed or ambiguous question. 1700+ questions are live across our active certifications, and every one of them passed this.
1 · Grounded in authoritative sources
Questions are generated from public-domain NIST publications (SP 800-53, 800-37, 800-61 and more) and official exam blueprints — not from copyrighted study guides. Each explanation cites its source so you can trace and trust it.
2 · Blind re-answered by two AI model families
Before any question goes live, two independent model families (Llama and GPT) answer it cold — without being told the intended answer. The question only passes if both independently choose the same answer and find no ambiguity. Correlated blind spots get caught.
3 · Held back on any disagreement
If the two models disagree, or either flags the question as ambiguous or factually off, it is held out of the live exam and queued for review. Wrong-keyed questions never reach you.
4 · Repaired with reasoning
Flagged questions are sent to a third adjudicator that re-solves them from scratch, then either corrects the answer key by consensus or reframes the question to remove the ambiguity — and re-verifies the result across both model families.
5 · Human-reviewed before the rest go live
Anything that still does not clear the automated bar lands in a human review queue with the full verdict and a proposed fix, so a person makes the final call on the hardest cases.
Why two model families instead of one
A single model that checks its own work tends to rubber-stamp its own mistakes. Two independent lineages making the same call is a far stronger signal — it catches the correlated errors a same-family double-check would miss.
Practice on questions you can trust
Grounded, cited, cross-checked by two AI models. Start free.
Start free