AI Infrastructure alternatives
The most-used ai infrastructure tools compared with Unstructured — 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 Unstructured.
AWS's fully managed service for accessing foundation models from multiple providers, with agents, guardrails, and knowledge bases built in.
Databricks' suite for building, governing, and serving production AI — agents, RAG, fine-tuning, and evaluation — on top of your governed data.
Microsoft Azure's managed access to OpenAI models, deployed within an enterprise Azure tenant with its security and compliance controls.
A platform for deploying and serving machine-learning models in production, with autoscaling, fast cold starts, and GPU infrastructure managed for you.
A developer-friendly open-source embedding database designed to make building retrieval and RAG prototypes fast and simple.
Google Cloud's unified AI platform — access to Gemini and partner models, plus tools to build, deploy, and govern AI and agents.
An inference provider whose custom LPU hardware delivers exceptionally low-latency responses for open-weight models.
An open-source LLM gateway that gives you one consistent API and proxy across 100+ model providers, with key management and spend tracking.
Browse our workflow library to see how each of these tools fits into real SMB automation stacks.