15 AI/ML Architecture Decision Records: Production-Ready, Cloud-Agnostic.
Stop documenting the same AI architecture decisions from scratch. 15 opinionated, production-ready ADRs covering the full AI/ML adoption lifecycle. Every decision includes context, options compared, rationale, and consequences.
15 documents: ready to implement.
AI/ML Framework Selection
PyTorch vs TensorFlow vs managed services: cloud-agnostic options comparison
Model Hosting Strategy
Third-party API vs managed endpoint vs self-hosted: tiered by data sensitivity
Training Data Storage and Governance
Object storage + DVC vs managed data platform: Privacy Act aligned
Model Versioning and Registry
MLflow vs cloud-native registry: experiment tracking, promotion workflow
Inference Infrastructure
Serverless vs real-time vs batch: tiered by traffic pattern and latency
AI/ML Observability and Monitoring
Drift detection, fairness monitoring, data quality: cloud-native + open source
Prompt Management and Engineering
Git vs dedicated prompt platform: version control, security, audit trail
RAG vs Fine-tuning vs Base Model
When to use each: cost, data requirements, privacy implications
Human-in-the-Loop Design Pattern
Risk-tiered oversight model: in-the-loop vs on-the-loop vs automated
Output Validation and Guardrails
Layered approach: provider safety + custom business logic + logging
Privacy and APP 8 Compliance
Pseudonymisation vs consent vs sovereign hosting: Privacy Act cross-border obligations
Model Provenance and Supplier Assessment
Tiered supplier assessment: Tier 1/2/3 by production use and data sensitivity
AI Incident Response and Rollback
Canary + automated rollback vs blue/green vs feature flag: per incident severity
Bias, Fairness, and Explainability
SHAP vs LIME vs inherent interpretability: regulatory and legal defensibility
AI Cost Optimisation Strategy
Per-feature tagging, prompt caching, serverless inference: 40-70% cost reduction approaches
What makes this different.
15 complete ADRs in one document
Every ADR includes context, decision drivers, options table with pros and cons, decision, rationale, and consequences.
Privacy Act APP 8 built in
ADR-ML-011 covers Australian cross-border AI processing obligations: pseudonymisation, consent, and sovereign hosting trade-offs.
Cloud-agnostic throughout
Options compare AWS, Azure, GCP, and cloud-agnostic open source alternatives. No single cloud assumed.
ISO 42001 aligned
ADRs reference relevant ISO 42001 Annex A controls where applicable: fairness, security, transparency, and third-party AI.
Editable DOCX
Adapt any ADR to your organisation's context. Modify decisions, add organisation-specific consequences, update dates.
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