Guides
End-to-end walkthroughs that combine Confident AI features in implementation workflows.
Overview
Guides are end-to-end walkthroughs for common Confident AI implementation workflows.
Use these guides when you want to see how multiple Confident AI features work together in a real setup, with the relevant code and configuration in one place.
End-to-End Guides
Choose a guide based on the workflow you want to implement:
Open a test run, stream your app’s traces into it as test cases, and let Confident AI evaluate each one at the trace and component level — over the API or OpenTelemetry.
Plan what leadership cares about, build it into a custom Executive Report template, and automate delivery so a curated report reaches your stakeholders on a schedule.
Set up distributed tracing for MCP hosts and servers, then evaluate whether your agent calls the right tools with the right arguments against a dataset before you ship.
Install the confident-client Agent Skill and drive the Admin SDK from Cursor, Claude Code, or Codex — creating projects, inviting members, and provisioning keys with plain-English prompts.
Use this guide to provision a dedicated Confident AI project for each agent your users build, then route its traces into the correct project.
Connect to an OAuth2-protected endpoint (Azure AD / Microsoft Entra ID or Auth0) by having Confident AI fetch a Bearer token before every request.
Evaluate agents that take minutes to respond by enabling Async Responses on your AI connection and posting results back through the Evals API.
Deploy the Confident Agent in an air-gapped or egress-restricted network using outbound-only WebSocket Secure (WSS) connectivity.
Use this guide to serve project-specific onboarding and governance instructions to Claude Code, Codex, Cursor, and other coding agents.
Additional guides for common implementation workflows will be added over time. To request a guide, contact support.