Production patterns for security copilots — handle refusals, fallbacks, and uncensored primary inference.
If your copilot returns empty strings on 200 OK, your users think the product is broken — because it is.
Instrument everything
Log stop_reason, stop_details.category, cyber_policy, token counts, served_model vs requested_model.
Fallback chains
Fable → Opus fallback helps some cases. Multiple vendor fallbacks add complexity. Uncensored primary simplifies.
Icelake as primary
Predictable completions for audit, IR, and detection rule drafts. OpenAI-compatible for drop-in.
Try uncensored AI free
No filters, no lecture, no training on your chats. Start in under a minute.
Security copilots fail quietly — design for loud failures and measurable completion rates.
FAQ
Is uncensored safe for enterprise?
Pair no-refusal models with your own policy, logging, and air-gapped deployment if required.