Design courses, assess student work, analyse programmes, and govern AI use β using a connected set of structured, inspectable tools across education and research.
These applications are usable, interactive tools designed as demonstration implementations that show how AI-supported workflows can be designed, analysed, and governed in practice. Full capability development is supported through structured courses and guided system design.
Not sure where to start or which tools to use?
The AI System Navigator guides you through your goal and recommends the right sequence of tools β from system definition through design, governance, and evidence.
βΒ Launch AI System Navigator
Apply these tools in real academic and research work through guided courses, structured workflows, and practical system design.
βΒ Start learning AI system design and governance
If you are new to CloudPedagogy, start with the guided route:
β Start with the AI System Navigator (recommended)
Or follow a manual pathway below based on your task.
Start by understanding structure, then test and refine it:
β Programme Governance Dashboard
β Curriculum Alignment Mapping Engine
β Curriculum Simulation ToolΒ
Design assessments, define AI use, and generate evidence:
β Assessment Design Engine
β AI Integrity Design Tool
β Evidence Pack GeneratorΒ
Diagnose capability, explore patterns, and identify risks:
β AI Capability Self-Assessment
β AI Capability Dashboard
β AI Capability Gaps & RiskΒ
Design workflows, assess risk, and record decisions:
β AI Workflow Governance Designer
β AI Governance Risk Scanner
β HumanβAI Decision Record ToolΒ
Understanding β Design β Assess β Simulate β Operate β Govern β Evidence β Evolve
Most workflows move through this sequence β you can enter at any stage depending on your needs.
Together, these applications provide full lifecycle coverage of AI-enabled academic and research systems β from understanding and design to governance, evidence, and continuous improvement.
All applications are open, inspectable, and available via GitHub:
https://github.com/cloudpedagogy
Each tool includes guidance on when to use it β select based on your task or context.
You can explore tools directly below β or use the AI System Navigator to be guided to the right ones.
This is the core system object that underpins all other tools.
These tools define the AI system being designed, assessed, and governed across the CloudPedagogy ecosystem.
β When to use: Define the structure, risks, and governance of an AI system before or alongside using other tools.
[Launch tool] Β· [View source]
Start here if you want to understand, diagnose, or govern AI capability before building or deploying systems.
These tools support understanding, developing, and governing AI capability across individuals, teams, and institutions.
Tools for diagnosing, mapping, and developing AI capability across educational and organisational contexts.
AI Capability Self-Assessment
β When to use: Understand your current AI capability and identify where to start.
[Launch tool] Β· [View source]
AI Capability Dashboard
β When to use: Explore and reflect on AI capability patterns across individuals or teams.
[Launch tool] Β· [View source]
AI Capability Gaps & Risk
β When to use: Identify capability gaps and associated risks in your organisation or practice.
[Launch tool] Β· [View source]
AI Capability Scenario Stress-Test
β When to use: Test how your systems or organisation respond under future or uncertain AI scenarios.
[Launch tool] Β· [View source]
AI Capability Programme Mapping
β When to use: Map how AI capability is developed across a curriculum or organisational structure.
[Launch tool] Β· [View source]
Tools for designing, analysing, and documenting humanβAI decision-making and governance structures.
AI Workflow Governance Designer
β When to use: Design and document AI-supported workflows with clear human oversight.
[Launch tool] Β· [View source]
AI Governance Risk Scanner
β When to use: Analyse risk, fragility, or oversight gaps in an AI-supported workflow.
[Launch tool] Β· [View source]
AI Assurance & Review System
β When to use: Review AI outputs, governance controls, grounding quality, operational risk, and oversight readiness before deployment or institutional use.
[Launch tool]Β Β·Β [View source]
HumanβAI Decision Record Tool
β When to use: Record and audit decisions where AI has influenced outcomes.
[Launch tool] Β· [View source]
AI Governance Maturity Assessment
β When to use: Assess organisational readiness to govern AI systems effectively.
[Launch tool] Β· [View source]
These tools support the design, analysis, and improvement of curriculum, programmes, and structured learning systems.
Tools for structuring, aligning, and simulating curriculum and programme-level design.
Programme Governance Dashboard
β When to use: Analyse programme-level structure, alignment, and governance readiness.
[Launch tool] Β· [View source]
Curriculum Alignment Mapping Engine
β When to use: Identify gaps, duplication, or misalignment across modules and learning outcomes.
[Launch tool] Β· [View source]
Pathway Personalisation Engine
β When to use: Explore and design learner pathways aligned to capability and progression.
[Launch tool] Β· [View source]
AI-Assisted Curriculum Refactoring Tool
β When to use: Improve and harmonise curriculum content using structured AI-supported workflows.
[Launch tool] Β· [View source]
Curriculum Simulation Tool
β When to use: Test curriculum structure, sequencing, and workload before implementation.
[Launch tool] Β· [View source]
Shared Module Repository System
β When to use: Manage reusable curriculum components across programmes.
[Launch tool] Β· [View source]
Video Learning Mapper
Transforms video transcripts into structured, reusable learning components aligned to curriculum and system design.
Enables conversion of unstructured teaching materials into organised inputs for curriculum development, analysis, and reuse.
β When to use: Convert video transcripts into structured inputs for curriculum design, analysis, and reusable learning content.
[Launch tool] Β· [View source]
These tools extend the ecosystem into AI-aware assessment design and academic integrity in an AI-enabled learning environment.
Assessment Design Engine
β When to use: Design structured, AI-aware assessments aligned to learning outcomes.
[Launch tool] Β· [View source]
AI Integrity Design Tool
β When to use: Define acceptable AI use in assessment and generate clear student guidance.
[Launch tool] Β· [View source]
These tools focus on structuring and governing AI-supported research workflows across the full research lifecycle.
Research Workflow Engine
β When to use: Design and document AI-enabled research workflows with governance and oversight.
[Launch tool] Β· [View source]
Use these tools to design, structure, and operationalise AI-enabled workflows in practice.
These tools support the practical application of AI-enabled workflows and capability development in academic environments.
AI Capability Studio
β When to use: Create structured workflow records aligned to the AI Capability Framework.
[Launch tool] Β· [View source]
These tools connect system design to institutional processes such as quality assurance, review, accreditation, and continuous improvement.
Evidence Pack Generator
β When to use: Generate structured evidence for quality assurance, accreditation, or review processes.
[Launch tool] Β· [View source]
Curriculum Change Manager
β When to use: Track, compare, and justify curriculum or assessment changes over time.
[Launch tool] Β· [View source]
These tools support data exchange, interoperability, and structured outputs across the CloudPedagogy ecosystem.
These are supporting infrastructure components rather than end-user tools.
Integration Tool
[Launch tool] Β· [View source]
Integration SDK
[View source]
Course Engine
[Learn more] Β· [View source]
These applications are part of a broader capability development approach, combining practical tools with structured learning to support individuals and institutions in building AI-ready practices.
π Explore courses: Β https://www.cloudpedagogy.com/pages/ai-courses
A complete guide to the CloudPedagogy AI Governance System, including its architecture, workflows, applications, and real-world use cases.
π CloudPedagogy AI Governance System Handbook.pdf
Most institutions are currently experimenting with AI in fragmented ways β isolated tools, disconnected pilots, and unclear governance.
CloudPedagogy provides a structured alternative:
π a system for making AI use visible, accountable, and aligned with institutional goals
π a way to move from experimentation to governable, scalable practice
π a platform for designing humanβAI systems that can be understood, reviewed, and improved over time
CloudPedagogy Applications are independent, exploratory tools developed outside any institutional role.
They are not affiliated with, endorsed by, or representative of any employer, university, or organisation.
All tools are provided for educational, experimental, and illustrative purposes only and do not constitute professional, legal, academic, or institutional advice.
These tools support structured reasoning but do not replace human judgement. Responsibility for interpretation and decisions remains entirely with the user.
Functionality, assumptions, and outputs may evolve over time.