Infra Recommendations

Use this page after modeling your costs. Optimize model and retrieval assumptions first, then compare infra providers with the same scenario in mind.

How to use this page

Run your scenario first in a tool and identify whether model, retrieval, or infra is really driving cost.
Explore provider options here only after your scenario assumptions are set.
Return to the tools to re-check margin after infra changes.

Related tools:

Provider Options

Compare provider fit only after you confirm that model choice, retrieval depth, reranking, or prompt context are not the bigger cost lever.

Disclosure: We earn commissions when you shop through the links below at no extra cost.

Vector database

Best for: Managed retrieval stacks where low-latency similarity search is on the hot path.
Choose it when: Retrieval quality and latency matter enough that a managed vector layer is simpler than building one into the app stack.
Skip it when: Your workflow is mostly chat-only, your corpus is small, or a simpler datastore already handles search well enough.
Pricing model: Usage-based vector infrastructure with index and capacity choices.
Lock-in level: Medium to high because retrieval design, indexing choices, and query paths become provider-shaped.

Managed vector database for embeddings, indexing, and low-latency similarity search.

Cloud hosting

Best for: Lean teams that want straightforward app hosting, databases, and general compute without a large cloud-control surface.
Choose it when: You want predictable app and database hosting for the surrounding product, not a specialized AI platform.
Skip it when: You already have deep commitments to another cloud or need niche managed services outside the core app stack.
Pricing model: Usage-based compute, storage, and managed-service pricing with simple instance tiers.
Lock-in level: Medium because hosting, networking, and managed database choices still shape migration effort.

Cloud hosting for app compute, databases, and the surrounding product stack.