What We Review
The architecture review covers four structural dimensions. Each one reveals a different category of risk.
Model Dependency Mapping
We document every external model dependency, assess single points of failure, and evaluate fallback coverage for each.
Pipeline Integrity
We review the full data and inference pipeline for structural fragility, race conditions, and failure propagation paths.
Integration Architecture
We assess how AI components integrate with the rest of your system, identifying coupling that creates operational risk.
Failure Mode Analysis
We model how the architecture fails — silently, loudly, or degraded — and document what each failure mode costs.
Related Services
Architecture review is often the starting point. It pairs naturally with a broader audit or governance design engagement.
Frequently Asked Questions
- What is an AI architecture review?
- An independent assessment of how AI components are structured in your product — covering model integration, pipeline design, dependency patterns, and failure modes.
- When should we do an architecture review?
- The best time is before scaling. The second-best time is after a major build phase, before a fundraise, or when unusual failure patterns start appearing.
- How is this different from an AI systems audit?
- The audit is broader and covers risk, governance, and code. The architecture review focuses specifically on structural decisions — how your AI is built, not just what it does.
- Do you need access to our cloud environment?
- No. We work from architecture documentation, infrastructure diagrams, and technical interviews. We do not require direct environment access.