Our approach to AI safety.

The problem with most AI assistants

Most conversational AI either runs with no guardrails and hopes for the best, or bolts on a single content filter and calls it compliance. Neither holds up when the AI is talking to your customers about coverage, medical questions, legal matters, or money.

Review the configured checks

Fred uses configured checks to evaluate messages and responses. Detected matches can trigger the configured action. Pattern checks can miss context or flag harmless content, so test and monitor the behavior you rely on.

Layered, not a flat list

Guardrails are composed in layers: universal safety rules for every conversation, then regional, industry, and your own custom rules on top. A healthcare practice in California gets different boundaries than a roofing company in Texas, resolved automatically from your configuration. Each rule defines what happens when it triggers, from adding a disclaimer to redirecting to a professional, flagging for review, or redacting, proportional to the risk.

Proactive, not just reactive

Compliance boundaries are built into Fred’s instructions from the first word of a conversation, so the goal is not to generate a bad answer and then fix it, it is to not go there in the first place. The after the fact check is the safety net, not the main mechanism.

Practical certainty

Fred uses layered rules and pattern-based detection for business conversations. Test realistic requests, including ambiguous phrasing and unsafe requests the checks might miss. Keep professional judgments with your team.

What it means for you

You do not need to understand any of this to use Fred. You pick your industry, enable the packs, and Fred handles the rest. If you are evaluating Fred for a regulated business and want a deeper walkthrough, book a call.