A local-first tool for designing, structuring, and governing AI-enabled research workflows across the full research lifecycle.
🌐 Live Hosted Version
http://cloudpedagogy-research-workflow-engine.s3-website.eu-west-2.amazonaws.com/
🖼️ Screenshot
Phase: Phase 5 — Practice & Workflow Layer
Role:
Supports the design and documentation of research workflows, including AI involvement, human oversight, risks, and reproducibility considerations.
Upstream Inputs:
- Research context defined by users
- Institutional policy and ethical considerations
Downstream Outputs:
- Structured workflow summaries for governance and review
- Inputs for the Evidence & QA Pack Generator
- Documentation for research transparency and reproducibility
Does NOT:
- Conduct research analysis
- Automate research execution
- Replace formal ethics review processes
The Research Workflow Engine enables researchers and academic teams to design structured, transparent, and governance-aware research workflows in an AI-enabled environment.
It supports:
- mapping research stages from design to dissemination
- documenting AI involvement at each stage
- defining human roles and oversight responsibilities
- capturing risks, ethics, and reproducibility considerations
This helps ensure research workflows are:
- transparent
- accountable
- reproducible
- aligned with institutional expectations
-
Workflow Stage Design
Define and sequence stages across the research lifecycle -
AI Involvement Mapping
Capture how AI is used at each stage -
Human Oversight Definition
Specify roles, responsibilities, and decision points -
Risk & Ethics Capture
Identify risks, ethical considerations, and constraints -
Reproducibility Support
Document methods, assumptions, and reproducibility notes
- Built with TypeScript + Vite (React)
- Fully local-first — runs entirely in the browser
- Uses localStorage for persistence
- Supports JSON import/export
- No backend or external data storage
npm install
npm run dev
npm run build
- Local-first and inspectable
- Governance-aware by design
- Structured, not automated decision-making
- Supports human judgement rather than replacing it
This repository contains exploratory, framework-aligned tools developed for reflection, learning, and discussion.
These tools are provided as-is and are not production systems, audits, or compliance instruments. Outputs are indicative only and should be interpreted using professional judgement.
- All applications run locally in the browser
- No user data is collected, stored, or transmitted
- All example data is synthetic and does not represent real institutions or programmes
CloudPedagogy develops open, governance-credible tools for building confident, responsible AI capability across education, research, and public service.
- Website: https://www.cloudpedagogy.com/
- Framework: https://github.com/cloudpedagogy/cloudpedagogy-ai-capability-framework
This tool supports both AI capability development and lightweight governance. Capability is developed through structured interaction with real workflows Governance is supported through optional fields that make assumptions, risks, and decisions visible All governance inputs are optional and designed to support — not constrain — professional judgement.