Building Scalable AI Solutions: Architecture Best Practices

Launching an AI feature is easy; keeping it fast, reliable, and cost-efficient at scale is the work. Here are the architecture patterns we use.

Data pipelines first

• Event streams for real-time signals; enforce schemas to avoid drift.
• Feature store to align training and serving.

Serving patterns

Guardrails, observability, cost

• Validation, filters, circuit breakers, fallbacks.
• Track latency p50/p95/p99, error rates, drift, and user feedback loops.
• Model routing, quotas, batching, caching to manage spend.