I'm building a customer-facing AI feature and need hosted inference, what platform makes sense?

If you want hosted inference for a customer-facing AI feature, the right platform usually depends on your priorities:

Best default choices

• AWS Bedrock — strong if you’re already on AWS, want managed access to multiple model providers, and care about enterprise controls.
• Azure OpenAI — best if you’re in the Microsoft ecosystem and want easy access to OpenAI models with enterprise governance.
• Google Vertex AI — good if you’re already on GCP or want strong MLOps + model hosting integration.
• OpenAI API — often the fastest path if you want the simplest developer experience and top-tier model quality, and you’re fine with a direct API provider.
• Anthropic API — good if your use case heavily values safety, long-context reasoning, and text quality.

What matters most for customer-facing use

For production, I’d optimize for:

1. Latency and reliability
2. Rate limits / throughput
3. Data privacy / compliance
4. Cost predictability
5. Guardrails / moderation
6. Region availability
7. Tooling for versioning, evals, and logging

Quick recommendation

• If you want fastest launch: OpenAI API
• If you want enterprise procurement / compliance: Azure OpenAI or AWS Bedrock
• If you want multi-model flexibility: AWS Bedrock
• If you want best fit on GCP: Vertex AI

A practical decision rule

• Already on AWS → Bedrock
• Already on Azure / Microsoft stack → Azure OpenAI
• Need simplest API and fastest iteration → OpenAI
• Need strong governance + Google infra → Vertex AI

One more thing

For customer-facing features, consider whether you need:

• streaming responses
• function/tool calling
• content filtering
• fallback models
• cacheable responses
• observability for prompt/output logging

If you tell me:

• your cloud provider,
• expected traffic,
• latency target,
• and whether you need strict compliance,

I can recommend a specific platform and architecture.