Recommended first
Getting Started
Bring up AI Governance Platform locally, make your first API call, and see your first governed result.
6 lessons~60 min
Start journey AI Governance Platform Academy
Go from first run to governed AI workflow.
Learn AI Governance Platform by building useful capabilities—not by sorting through documentation. Choose a path, complete the missions, and see what you can build next.
01
Set up locally
02
Observe evidence
03
Evaluate safely
04
Replay with confidence
Start with an outcome
Learning Paths
Structured routes that get you to a working capability, with each lesson building on the last.
Guided next
Governance Fundamentals
Understand observed assets, evaluations, policies, decisions, and evidence lineage.
5 lessons~75 min
Explore path Guided next
Replay Engineering
Build production-grade replay workflows from frozen evidence through comparison and drift.
4 lessons~70 min
Explore path Mission-based practice
Walkthrough Missions
Dedicated, step-by-step guides. The Academy records your manual progress in this browser; Local Studio validates the live stack after you choose to open it.
MISSION #01 15 min
Observe prompt & model assets
Record the runtime prompt and model evidence behind an AI interaction.
You will learn
- Asset Registry
- Runtime observation
- Evidence lineage
MISSION #02 15 min
Review a governance decision
Trace a decision from its policy outcome to its evidence and lineage.
You will learn
- Policy outcomes
- Decision lineage
- Studio reviews
MISSION #03 10 min
Run a governed replay
Prepare a replay from governed evidence and inspect its normal lifecycle in Studio.
You will learn
- Replay preparation
- Run lineage
- Reusable manifests
Build, don’t just browse
Map
Your map reflects the capabilities a path builds. Use it to choose the most useful next step for the system you’re making.
REST API
MCP
Assets
Evaluations
Governance
Replay
Ontology
Impact Analysis
Behavior Contracts
Recommendations
Enterprise Events
Start with Getting Started to activate your core capabilities, then follow the highlighted next path.
All guides
Tutorial Library
Prefer to jump straight to a specific topic? Every practical guide is still here, searchable through your browser and ready when you need it.
Getting Started
Local Developer Workflow
Start Keycloak, REST, MCPO, Studio, Neo4j, demo seed data, and worker health in the supported local workflow.
Beginner15 min
Prerequisites
Python 3.12+ · uv · Docker for infrastructure
Operations
Docker Deployment
Stand up the full stack: REST API, Studio, and Neo4j with managed datastores.
Advanced20 min
Prerequisites
Docker installed
Interfaces
Governed Replay Walkthrough
Follow one API-driven product path from observed runtime evidence through evaluation, governance, replay preparation, lineage, and a reusable run manifest.
Beginner10 min
Prerequisites
AI Governance Platform local stack running · Seeded demo data · Python 3.12+
Interfaces
AI Governance Platform Walkthrough Quests
Use versioned, public-API terminal journeys for evaluation evidence, policy gates, governance decisions, experiment outcomes, and governed replay.
Beginner10 min
Prerequisites
AI Governance Platform local stack running · Seeded demo data · Python 3.12+
Interfaces
Observed Prompt and Model Assets
Report runtime prompt and model evidence to AI Governance Platform without moving prompt authoring or model serving into the control plane.
Intermediate15 min
Prerequisites
AI Governance Platform API running · Runtime or evaluation producer · API token
Governance
Review Governance Decisions
Inspect a decision outcome, validate its evidence graph, follow ontology lineage, and record a defensible review conclusion in Studio.
Beginner15 min
Prerequisites
Studio running · Seeded data or a persisted decision
Governance
Governance Insights
Explore experiment insights, candidate explanations, drift analysis, investigations, and report generation.
Intermediate30 min
Prerequisites
Experiments and evaluations created · API running
Studio
Studio - Experiment Management
Register governed candidates, run evaluations, compare configurations and metrics, and inspect leaderboard recommendations in Studio.
Beginner20 min
Prerequisites
Studio running · Seeded data or governed registry assets
Studio
Studio - Replay Management
Reproduce a historical execution from frozen evidence, follow worker execution, and review comparison and drift results.
Intermediate25 min
Prerequisites
AI Governance Platform API and worker running · Replayable historical execution
Interfaces
MCP Server Basics
Learn the AI Governance Platform MCP foundations, from direct calls and stdio to native Streamable HTTP and MCPO.
Beginner20 min
Prerequisites
AI Governance Platform API running · Python 3.12+
Interfaces
Native MCP Streamable HTTP
Connect MCP-aware clients over HTTP with a Keycloak bearer token, then validate the setup in MCP Inspector.
Intermediate20 min
Prerequisites
AI Governance Platform local stack running · Python 3.12+
Interfaces
MCP Controlled Writes
Submit evaluations, create experiments, and manage jobs through the MCP server with full audit trails.
Intermediate25 min
Prerequisites
MCP server basics · AI Governance Platform API running
Getting Started
REST Control Plane
Explore the full REST API surface: health checks, evaluations, governance comparisons, experiments, and job management.
Beginner15 min
Prerequisites
Docker Compose running · API on localhost:8000
Operations
Operate Neo4j Synchronization
Inspect graph projection health, diagnose synchronization events, and safely retry a dead-letter event in Studio.
Intermediate20 min
Prerequisites
Docker Compose running · Seeded data