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Introduction

Genum.ai is a powerful, AI-native platform for designing, testing, and managing prompt-based systems at scale. It introduces a cutting-edge Prompt Ops Layer called Genum Lab, which turns conversational intent into robust AI specifications—automatically versioned, testable, and production-ready.

The Big Problem​

Today, prompts are often treated as messy, unstructured text files—lacking any form of version control, testing, or operational standards. As AI models become more powerful, prompts are increasingly becoming the core holders of business logic. In many cases, even orchestration logic will eventually migrate into prompts.

Yet, despite this critical role, prompts are still unmanaged artifacts. There is no accepted standard to convert natural language intent into structured, testable, versioned AI specifications.

Genum Lab solves this by introducing CI/CD for prompts—enforcing structure, testability, and traceability, and turning prompts into first-class operational artifacts.

Prompt CI/CD

Key Capabilities​

  • Natural Language Prompt Authoring
    Capture user intent through natural language and convert it into structured, reusable AI specifications.

  • Integrated Regression Testing
    Validate prompt behavior over time by saving test cases and comparing outputs against expected results.

  • Version Control
    Commit, rollback, and compare prompt versions with complete metadata, including model configurations.

  • Audit Logging
    Every prompt execution is logged with full context—inputs, outputs, model metadata, timestamps, and more.

  • FinOps Insights
    Monitor token usage, cost, performance metrics, and user activity through a unified dashboard.

  • Multi-Agent AI Orchestration
    Use specialized agents for prompt generation, validation, auditing, and commit messaging—completely automated.

  • Vendor-Agnostic Runtime
    Design prompts and test suites for multiple AI providers (OpenAI, GNI, Gemini), with full support for custom output schemas and execution tooling.

  • Integration by Design
    Trigger prompts using HTTP endpoints or custom runtime nodes (e.g., for n8n, Make, Zapier) and process input/output through validated AI specifications.

Explore the rest of the documentation to learn how to build, validate, and scale high-performance AI workflows with confidence and transparency.