Reqvire is the lightweight Git-native Requirements As a Code framework that transforms how modern engineering teams build software. Seamlessly blending system modeling, requirements management, and AI-assisted development. Reqvire empowers teams to deliver better products faster with complete traceability and intelligent automation.

Experience the future of development where your requirements live alongside your code, evolve with your project, and unlock the full potential of AI-powered engineering—from intelligent requirement synthesis to automated code generation—all within your familiar Git workflow.

Reqvire unlocks:

  • 🚀 Requirements as Code: Transform requirements from static documents into living, version-controlled assets that evolve with your codebase
  • ⚡ Effortless Integration: Plug seamlessly into your existing workflow with Git branches, pull requests, and CI/CD pipelines—no disruption, just enhancement
  • 🤖 Smart Automation: Reqvire handles diagram generation, traceability matrices, and impact analysis automatically—your requirements become high-quality context for AI tools
  • 🧠 AI-Ready Architecture: Optimal context that enables AI assisted requirements management and assisted coding—AI understands what needs to be built, where to make changes, and how everything connects

Reqvire Modeling Language

Reqvire uses a lightweight, opinionated modeling language based on semi-structured Markdown.

Why Markdown Matters

By sticking to a semi-structured Markdown format:

  • AI tools don’t need complex parsers or DSL interpreters
  • Models can be used as-is by LLMs like ChatGPT, Claude, or private copilots
  • Validation and generation become trivial to automate

This makes Reqvire models not only powerful for humans but highly interoperable with AI systems, whether embedded in CI/CD, editors, or code review bots.

Key Elements

Each Reqvire model is made up of Markdown files and elements representing:

  • Requirements – User needs, constraints, and system-level behaviors.
  • System Structure – Components, modules, and their interconnections.
  • Behaviors – States, flows, and operations.
  • Traceability Links – Relations between requirements, architecture, and test cases.
  • Verification Definitions – Mappings between requirements and their validation/test strategies.

These documents are written using simple conventions, headers, and embedded tags.

AI Compatibility

Reqvire is built to be AI-friendly from the ground up.

Example AI Use Cases

1. Requirement Analysis

LLMs can analyze Markdown-based requirements to identify missing elements, suggest clearer phrasing, propose edge cases, and generate acceptance criteria or verification steps.

2. Architecture Suggestion

By understanding relationships in architecture files, AI can detect inconsistent component relationships, propose modular design improvements, and suggest missing interfaces or dependencies.

3. Traceability & Impact Prediction

AI tools can automatically trace which tests or requirements are impacted by changes, flag affected downstream areas, and summarize model diffs for engineering teams.

4. Test Coverage Assistance

Based on requirements and use cases, AI can recommend missing test scenarios and create verifications based on test criteria extracted from requirements chain.

5. Code Generation Assistance

AI can leverage structured requirements for:

  • Context-Aware Generation: Understanding the “why” behind every component through Reqvire’s traceability structure
  • Specification-Driven Coding: Generating code directly tied to specific requirements, reducing guesswork or misinterpretation
  • Verification-Backed Validation: Referring to defined verifications to ensure implementation meets intended behavior
  • Trace-Based Refactoring: Assisting in propagating requirement changes through the codebase and related artifacts

6. Report Generation

AI can automatically generate traceability reports, summarize system architecture, and prepare documentation for releases or reviews.

Human in Control — Always

While Reqvire empowers AI tools to act as smart collaborators, the human engineer remains the system’s captain — setting direction, making decisions, and approving outcomes.

Reqvire ensures that:

  • Every AI-suggested change is traceable and reviewable
  • System evolution remains understandable and documented
  • AI tooling acts in service of the engineer’s intent, not in place of it

Diagram & Traceability Automation

Reqvire automatically parses structured Markdown to generate:

  • Architecture diagrams (component hierarchies, interfaces, dependencies)
  • Traceability matrices linking requirements to architecture, verifications, and tests
  • Impact reports showing what was changed, and what it affects
  • Requirement flow diagrams visualizing hierarchical relationships and derivations
  • Verification coverage maps showing which leaf requirements are verified and how
  • Change propagation analysis identifying all downstream effects of modifications
  • Compliance matrices mapping requirements to standards, regulations, or policies
  • Model summary reports providing overview statistics and health metrics
  • Interactive documentation with clickable diagrams and searchable content

CI/CD Integration

Reqvire is designed for automation. In typical Git-based workflows, you can:

  • Validate Markdown structure using static checks
  • Auto-generate diagrams during CI builds or PRs
  • Generate traceability and change impact reports for stakeholder review
  • Block PRs if requirements are incomplete or broken
  • Package models into versioned documentation releases