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AI Inference

Deploy and run serverless AI inference for LLMs, VLMs, embeddings, and multimodal models with an OpenAI-compatible API. Deliver faster user experiences on distributed infrastructure, with automatic scaling and no GPU clusters to manage.

Faster than traditional clouds

Tokens per second output speed

Lower latency

Low-latency inference for real-time user experiences

Keep time-to-first-token and end-to-end latency low with distributed execution. Built for interactive applications, streaming responses, and real-time decisioning.

Serverless scaling without GPU operations

Handle spiky demand without provisioning GPU clusters. Scale automatically from first request to peak load, while keeping costs aligned with usage.

Reliable by design for production workloads

Run mission-critical inference with distributed architecture and automatic failover, designed to keep AI features available when traffic spikes or regions fail.

"With Azion, we’ve been able to scale our proprietary AI models without worrying about infrastructure. These solutions inspect millions of websites daily, detect and neutralize threats with speed and precision, and execute the fastest automatic takedown in the market."

Fabio Ramos

CEO

Build, customize, and serve AI models in production

OpenAI-compatible API for serverless AI inference

Deploy production endpoints for LLMs, VLMs, embeddings, OCR, and image generation, then integrate them into Applications and Functions for distributed execution.

LLMs & VLMsFunctions integrationOpenAI-compatibleAuto-scaling

functions/ai-handler.js

1async function handleRequest(request) {
2  const input = await request.body()
3  const messages = input.messages
4 
5  const response = await Azion.AI.run('Qwen/Qwen3-30B-A3B-Instruct-2507-FP8', {
6    "messages": messages,
7    "stream": input.stream
8  })
9}

Docs

Execution of AI models with distributed architecture.

Fine-tune with LoRA for domain-specific performance

Fine-tune open-source models with Low-Rank Adaptation (LoRA) to adapt outputs to your domain without full retraining.

Improve quality for specific tasks like classification, extraction, retrieval, and support workflows while reducing compute requirements.

LoRA fine-tuningDomain customizationNo full retrainingLower compute costs

See how

Fine-tune AI models using LoRA for customization.

What you can build with AI Inference

Automation

AI agents for automated workflows

Deploy autonomous AI agents that plan, call tools, and take actions across your systems. Use tool calling to integrate external services and combine with Retrieval-Augmented Generation (RAG) patterns for grounded outputs.

AI Apps

AI-powered applications (RAG + search)

Combine AI Inference with Applications, Functions, and SQL Database vector search to build RAG, semantic search, personalization, and real-time user experiences with distributed execution.

Support

Customer support copilot

Serve a support copilot that answers in real time from your knowledge base, with streaming responses and high concurrency without managing GPU infrastructure. Pair with SQL Database vector search for grounded answers.

Security

Automated threat detection and takedown

Use LLMs and vision-language models (VLMs) to detect phishing and brand abuse, classify threats, and automate takedown workflows across distributed systems, designed for low-latency, real-time decisioning.

Frequently Asked Questions

What is Azion AI Inference?

Azion AI Inference is a serverless platform for deploying and running AI models globally. Key features include: OpenAI-compatible API for easy migration, support for LLMs, VLMs, embeddings, and reranking, automatic scaling without GPU management, and low-latency distributed execution. Create production endpoints and integrate them into Applications and Functions.

Which models can I run?

You can choose from a catalog of open-source models available in AI Inference. The catalog includes different model types for common workloads (text and code generation, vision-language, embeddings, and reranking) and evolves as new models become available.

Is it compatible with the OpenAI API?

Yes. AI Inference supports an OpenAI-compatible API format, so you can keep your client SDKs and integration patterns and migrate by updating the base URL and credentials. See the product documentation: https://www.azion.com/en/documentation/products/ai/ai-inference/

Can I fine-tune models?

Yes. AI Inference supports model customization with Low-Rank Adaptation (LoRA), so you can specialize open-source models for your domain without full retraining. Starter guide: https://www.azion.com/en/documentation/products/guides/ai-inference-starter-kit/

How do I build RAG and semantic search?

Use AI Inference with SQL Database Vector Search to store embeddings and retrieve relevant context for Retrieval-Augmented Generation (RAG). This enables semantic search and hybrid search patterns without additional infrastructure.

Can I build AI agents and tool-calling workflows?

Yes. AI Inference can be used to power agent patterns (for example, ReAct) and tool-calling workflows when combined with Applications, Functions, and external tools. Azion also provides templates and guides for LangChain/LangGraph-based agents.

How do I deploy AI inference into my application?

Create an AI Inference endpoint and integrate it into your request flow using Applications and Functions. This lets you add AI capabilities to existing APIs and user experiences with distributed execution and managed scaling.

Access to all features.
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