Name: SUPERWISE v1.27: self-service platform and full guardrails
Uploaded: 2025-12-02T00:00:00Z
Duration: 3 min 8 s
Description: Review the SUPERWISE v1.27 announcement, including built-in guardrails and Remote MCP support for deploying and governing AI agents.

Question 1

Where can I get SUPERWISE Sentinel?

Accepted Answer

Get Sentinel at /sentinel/windows/#get-sentinel to protect ChatGPT and Claude on Windows.

Question 2

How do guardrails work in SUPERWISE?

Accepted Answer

SUPERWISE guardrails are designed for using public models safely. They are rule-based policies that combine one or more rules to keep LLM outputs safe and accurate. You define them independently from agents, manage version history, and use a playground to test under different inputs and outputs before publishing. You can block when a rule is violated or let it through and audit it, with visibility into usage. See docs.superwise.ai/docs/guardrails-1.

Question 3

What is MCP integration in SUPERWISE?

Accepted Answer

MCP (Model Context Protocol) is the standard for exposing agent capabilities. SUPERWISE supports remote MCP with configurable header parameters for authentication so you can connect and govern MCP-based agents in one place.

Question 4

Why does governed AI need a guardrail playground?

Accepted Answer

A playground lets you test how rules apply to different values before going live. Governed AI requires that you verify behavior in advance and revisit published versions. SUPERWISE gives you that control so violations are caught during design.

Question 5

Does SUPERWISE support private or open-source models for PII and PHI?

Accepted Answer

Yes. SUPERWISE guardrails are designed for using public models safely. SUPERWISE also supports privately hosted and open-source models so customers can build sophisticated AI solutions that handle PII and PHI while keeping data in their control.

SUPERWISE v1.27: self-service platform and full guardrails

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