AI Infrastructure
AI infrastructure built for production reality.
Vector stores, retrieval, evals, observability, and platform engineering for AI systems.
What this engagement is.
SAZ AI infrastructure work stands up the platform AI systems need to run in production at scale — vector stores, retrieval, evals, observability, deployment, and governance.
What you should expect.
Outcome-led scoping — every engagement is measured against specific business outcomes.
- A production AI platform
- Retrieval, evals, and observability
- Governance and access controls
- A developer experience that compounds
What the team brings.
Vector & Retrieval
Pinecone, Weaviate, pgvector, custom — picked for fit.
Evals
Offline and online evaluation systems.
Observability
Latency, cost, quality, and drift.
Developer Platform
SDKs, templates, and deployment.
How an engagement runs.
Audit
Current state and use cases.
Architect
Platform architecture.
Build
Ship the platform in waves.
Questions buyers ask.
AI Infrastructure across Canada.
SAZ delivers this engagement across our Canadian footprint — from Vancouver to Halifax.
Engagements that pair with this.
AI Implementation
Hands-on engineering teams that ship production-grade AI systems on your stack.
Data Systems
End-to-end data systems: warehousing, pipelines, modeling, governance, and analytics.
Cloud Consulting
Cloud architecture, migration, FinOps, and platform engineering across AWS, GCP, and Azure.
Want to scope a AI Infrastructure engagement?
A senior partner will respond within one business day.