AI Infrastructure alternatives
The most-used ai infrastructure tools compared with Exa — pricing, strengths, and who each one is best for.
Each tool below is a same-category competitor. Click Compare for a side-by-side breakdown against Exa.
AWS's fully managed service for accessing foundation models from multiple providers, with agents, guardrails, and knowledge bases built in.
Microsoft Azure's managed access to OpenAI models, deployed within an enterprise Azure tenant with its security and compliance controls.
Turns any website into clean, structured markdown or JSON for AI pipelines — scrape, crawl, map, and search with published per-credit pricing.
Google Cloud's unified AI platform — access to Gemini and partner models, plus tools to build, deploy, and govern AI and agents.
A unified API and marketplace that routes requests to hundreds of models from many providers through a single endpoint and bill.
Give an agent a natural-language task and it drives a real browser to completion — open source library, or managed cloud browsers.
Databricks' suite for building, governing, and serving production AI — agents, RAG, fine-tuning, and evaluation — on top of your governed data.
AWS framework-agnostic runtime for deploying, securing, evaluating, and governing production agents at scale.
One AI workflow a week, with the AI Infrastructure that actually ship it — real stacks, real costs, and where each option falls down.
Browse our workflow library to see how each of these tools fits into real SMB automation stacks.