Backed by
Real-time robust AI hallucination detection.
Backed by
A query is submitted to a frontier model. While the response is generated, our analysis suite is activated.
Probing classifiers inspect the frontier model's outputs. This detects when a model is 'uncertain' in real time.
The response from the frontier model is returned with a clear trust indicator obtained from our analysis model.
Protect teams from hallucinated case citations, misquoted statutes, and fabricated facts. A safety net for AI-assisted research and drafting.
Ensure AI outputs in regulated workflows meet the bar for accuracy. Know which responses can be relied on and which need checking.
Integrate Scanf as a verification layer in your AI product. Differentiate on reliability and give your users confidence in every output.
Try Scanf and see real-time hallucination detection for yourself or reach out to talk about your use case.
