FDE Mastery is a governed execution platform for teams building, integrating, and operating enterprise AI agents and workflows.
It provides reusable identity and tenancy boundaries, agent execution, durable workflows, policy enforcement, human approvals, model and tool gateways, evaluations, observability, and operational controls across eight enterprise domains.
The diagram describes platform boundaries; it is not a screenshot or live deployment demonstration. See the architecture guide.
| Concern | Platform approach |
|---|---|
| Identity and tenancy | Tenant-aware identity context, scoped authorization and PostgreSQL RLS foundations |
| Agent execution | Versioned agent lifecycle, budgets, checkpoints and durable workflow boundaries |
| Consequential actions | Independent trust/policy controls, risk tiers and expiring human approvals |
| Tool and model access | Registries, capability boundaries, policy checks and provider adapters |
| Reliability | Leased work, retries, recovery, idempotency and incident lifecycle contracts |
| Evaluation | Golden and adversarial datasets, quality/safety gates and drift signals |
| Operations | OpenTelemetry-compatible observability, tenant-aware FinOps and deployment controls |
| Supply chain | CI security checks, SBOM generation, image signing and build provenance |
FDE Mastery is a modular monolith with explicit control-plane, data-plane and trust-plane boundaries. It does not split components into microservices before independent scaling or isolation is justified.
Run the repository tests with local in-memory and mock-provider settings. No production credentials are required.
git clone https://github.com/LloydCoder/fde-mastery.git && cd fde-mastery/packages/platform-core
python -m venv .venv && source .venv/bin/activate
python -m pip install -e ".[test]"
FDE_STORAGE_BACKEND=memory FDE_RATE_LIMIT_BACKEND=memory FDE_MONTH1_PROVIDER=mock MOCK_LLM=true FDE_ENVIRONMENT=test python -m pytest -qWindows PowerShell activation uses .venv\Scripts\Activate.ps1. Python 3.11 matches the primary CI runtime; package metadata supports Python 3.10 and newer.
| Tool | Requirement |
|---|---|
| Python | 3.10+; Python 3.11 is the CI baseline |
| Git | Required to clone |
| Docker Compose | Optional, for container deployment |
| Node.js | 20+ for the TypeScript SDK |
From packages/platform-core, install the platform and quality tools:
python -m pip install -e ".[test,quality,security,observability,sbom]"Optional dependency groups are defined in pyproject.toml. The production-oriented Compose definition is deployment/docker-compose.production.yml. It requires deployment-specific PostgreSQL, OIDC, application/admin key and managed-secret configuration. Follow the deployment guide; never use example credentials in production.
From the repository root:
PYTHONPATH=packages/platform-core python -m platformctl manifest
PYTHONPATH=packages/platform-core python -m platformctl doctorAfter installing the package, from packages/platform-core:
FDE_STORAGE_BACKEND=memory FDE_RATE_LIMIT_BACKEND=memory FDE_MONTH1_PROVIDER=mock MOCK_LLM=true FDE_ENVIRONMENT=test python -m uvicorn deployment.api_gateway.main:app --host 127.0.0.1 --port 8000In another terminal:
curl --fail http://127.0.0.1:8000/v1/healthSee API reference for authentication, tenant binding, idempotency and request metadata. Do not send customer data to a local test configuration.
| SDK | Runtime | Source |
|---|---|---|
| Python | Python 3.10+; standard-library HTTP client | sdks/python |
| TypeScript | Node.js 20+ | sdks/typescript |
The tracked API gateway example is .env.example. It contains placeholders only. Copy values into an untracked environment file and replace every placeholder before use.
| Variable | Template example | Purpose |
|---|---|---|
FDE_API_KEYS |
Placeholder | Application API keys |
FDE_ADMIN_API_KEYS |
Placeholder | Separate administrator API keys |
FDE_STORAGE_BACKEND |
memory |
Storage adapter |
FDE_DATABASE_URL |
Local PostgreSQL URL | Durable database connection |
FDE_DB_CREATE_TABLES |
false |
Automatic table creation |
FDE_RATE_LIMIT_BACKEND |
memory |
Rate-limit backend |
FDE_REDIS_URL |
Local Redis URL | Redis connection |
FDE_RATE_LIMIT_WINDOW_SECONDS |
60 |
Rate-limit window |
FDE_RATE_LIMIT_REQUESTS |
60 |
Request allowance |
FDE_MAX_BODY_BYTES |
262144 |
Maximum request body size |
See Configuration reference. Template values are not production recommendations.
| Domain | Example workflow |
|---|---|
| Cybersecurity | SIEM alert enrichment and SOC triage |
| Finance | Transaction risk and governance |
| HealthTech | Compliance and triage support |
| Logistics | Supply-chain risk analysis |
| Legal | Contract risk workflows |
| RevOps | Pipeline and account operations |
| Procurement | Supplier risk and quote comparison |
| Custom | Tenant-defined workflows and policies |
The platform provides versioned agent/tool/model/policy registries, durable workflows, tenant-scoped events, evaluation, incident management, AI FinOps, integration and interoperability boundaries, and deployment profiles.
High-impact actions remain subject to policy and human approval. Procurement is recommendation-oriented: the platform does not autonomously award suppliers, create purchase orders, modify vendor master data or approve spend.
These are reusable platform capabilities and reference integrations. They are not a security certification, regulatory approval or evidence of a live customer deployment.
| Guide | Description |
|---|---|
| Documentation index | Documentation map and reading paths |
| Getting started | Local setup and first checks |
| Architecture | Platform boundaries and dependency rules |
| Architecture decisions | Accepted architecture decision records |
| API and SDKs | Versioned API and client contracts |
| Configuration | Runtime environment settings |
| Deployment | Deployment model and operations |
| Production readiness | Eight-gate promotion model |
| Build status | Historical implementation and verification ledger |
| Security standards | Engineering control references |
| AI threat model | AI-specific threat considerations |
Issues and pull requests are welcome. Read CONTRIBUTING.md, follow the Code of Conduct, and use the provided templates.
FDE Mastery is distributed under the Apache License 2.0. The project uses and is informed by OWASP, NIST AI RMF, OpenTelemetry, CycloneDX, Sigstore Cosign and SLSA provenance.
Domain examples use synthetic or illustrative data. They are not financial, medical or legal advice. Customer deployments require their own threat model, data-protection decisions, integration validation, evaluation evidence, security review, operational runbooks and approval policy.
Support and troubleshooting
- Defects: GitHub Issues.
- Vulnerabilities: follow SECURITY.md; do not publish exploit details.
- Setup: see Getting started and Configuration.
- Deployment: see DEPLOYMENT.md.