AI knowledge cutoff & freshness checker
AI models confidently answer questions about topics they may know nothing current about. Each model has a training cutoff date, and anything that changed after it is invisible to the model unless it browses the web. This tool estimates how risky that gap is for your specific question by comparing the model’s cutoff to how quickly your topic category tends to change, then tells you what to verify.
How it works
You select the AI model you are using and the category your topic falls into. The tool looks up the model’s approximate knowledge cutoff and combines it with a volatility rating for the category — software versions and prices change fast, historical facts barely change at all. It then reports a freshness risk level: low for stable topics well within the cutoff, high for fast-moving topics that likely shifted after training. For higher-risk results it lists concrete verification steps. Everything runs locally in your browser.
Tips and notes
- Confidence is not currency. A fluent, specific answer can still be based on stale training data.
- Force fresh sources for live facts. Ask the model to browse, or paste in current data yourself, for prices, versions, and current events.
- Stable topics rarely need checking. Math, definitions, and established history sit safely inside any recent cutoff.
- Re-verify near the edge. If your topic changed just before or after the cutoff, double-check even “low” results.