AI governance for agentic AI: a setup walkthrough
Follow a SUPERWISE agent setup from data source and knowledge base through guardrails, Slack policy alerts, publishing, and observability.
What's in this video
- Connect a data source and create an agent with a prompt and knowledge base.
- Add input and output guardrails, then publish the agent.
- Send policy alerts to Slack and build an observability dashboard.
Frequently asked questions
Topics from this video and why governed AI matters.
- Why should I trust my AI?
- Ungoverned AI can produce unreliable or harmful outputs. SUPERWISE guardrails are designed for using public models safely. SUPERWISE also supports privately hosted and open-source models so you can build sophisticated AI solutions that handle PII and PHI. You connect to a secure data source and add guardrails and policies so you control what the agent accesses and how it behaves. Trust comes from control and visibility.
- What does the SUPERWISE Starter edition include?
- Starter is free with no credit card: runtime guardrails and policies, real-time visibility to AI decisions, governance experts via office hours, and Discord and GitHub communities. docs.superwise.ai offers guides, tutorials, and API references so you can integrate, manage, and scale AI operations from building agents and monitoring data to deploying with built-in safety guardrails.
- How do guardrails and policies improve trust?
- Guardrails and policies triple-check inputs and outputs before they reach users or systems. That reduces bad answers, data leakage, and compliance risk. Governed AI requires checks at runtime and during design.
- Why is governed AI critical for agentic AI?
- Agentic AI automates decisions and workflows. Without governance, you cannot prove safety or compliance. SUPERWISE gives you guardrails, visibility, and documentation so you deploy agentic AI with evidence.
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