Documentation Index

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FAQs
Glossary

    FAQs

      • How do I Evaluate AI Agents and Agentic Workflows?
      • How do I Create a Custom Evaluator?
      • How does Agent Simulation Help Evaluate AI Agents?
      • How can I Evaluate Voice AI Agents?
      • How can I Evaluate Local AI Agents?
      • What is AI Agent Evaluation?
      • How does Maxim AI Evaluate Multi-Turn Agent Trajectories Before Deployment?
      • What Types of Evaluators does Maxim Provide?
      • How do I Integrate Evaluations into my CI/CD Pipeline?
      • Can I Curate and Evolve Datasets for Agent Evals in Maxim?
      • Does Maxim Support Human-in-the-Loop Evaluation for Agents?
      • What is Agent Simulation?
      • What is LLM-as-a-Judge Evaluation?
      • How can I Detect Hallucinations in My AI Applications?
      • How can I Evaluate My RAG Application?
    Simulation and Evaluation

    How do I Integrate Evaluations into my CI/CD Pipeline?

    Maxim enables teams to build automated evaluation pipelines that integrate directly into CI/CD workflows to validate quality on every code or prompt change. The integration is powered by Maxim’s SDKs (Python, TypeScript, Java, and Go) and REST APIs, allowing teams to programmatically trigger test runs. Maxim integrates with popular CI/CD systems, including GitHub Actions, Jenkins, and CircleCI. Teams can automate both prompt and agent evaluations to catch regressions and enforce quality checks before any change reaches production.
    For implementation examples, step-by-step guides, and best practices, developers can reference the official documentation or GitHub repository.

    (See: Learn more about it here.)

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