A New Era for AI Deployments
Today, we’re announcing the launch of Azion AI Inference, our product that brings model flexibility and cost efficiency to artificial intelligence (AI) solutions, enabling businesses to easily build and adapt AI-driven applications to meet evolving needs. As AI models grow increasingly sophisticated and businesses demand real-time insights, the way you deploy and run these models becomes critically important. AI Inference transforms how organizations implement AI at scale, enabling them to run closer to the end users.
Azion AI Inference combines artificial intelligence with edge computing, allowing AI models to run directly on Azion’s distributed infrastructure—close to data sources and users—rather than in distant cloud data centers. This approach offers several advantages, such as reduced latency, enhancement of real-time processing capabilities, and overall application performance improvement while maintaining data privacy and reducing bandwidth consumption.
Why Traditional Cloud AI Deployments Fall Short
Modern AI models, such as Visual Language Models (VLMs) and Large Language Models (LLMs), face significant challenges when deployed in traditional cloud environments, making it hard to meet the needs of time-sensitive applications. Although these models have evolved to run faster, the inherent distance between users and cloud data centers still causes unavoidable latency issues, as requests must travel to remote servers for processing and then back to the users.
Cloud-based AI implementations suffer from complex container-based deployment and management, as well as unpredictable performance due to bandwidth constraints, geographic distances, and resource contention. These issues are problematic for all kinds of applications, especially time-sensitive ones like fraud detection, which require continuous updates and consistent, rapid responses.
Last but not least, cloud costs are now well-known as a key problem to address in every application designed to scale.
AI Inference: Transforming AI Deployment
AI Inference addresses these fundamental challenges by bringing AI computation directly to a globally distributed network. Our solution enables:
Comprehensive AI Capabilities at the Edge
With Azion AI Inference, you can execute a diverse ecosystem of AI models on our highly distributed network. Our platform supports:
- Large Language Models (LLMs)
- Vision Language Models (VLMs)
- Multimodal architectures
- Embedding models
- Reranking models
And more - all running with minimal latency. Read our Runtime documentation for more information.
Beyond model execution, AI Inference enables advanced AI workflows including reasoning, audio, text, and image conversions, as well as tool calling capabilities. The platform supports model customization through Low-Rank Adaptation (LoRA), allowing you to fine-tune models for your specific business needs. All these capabilities integrate with your edge applications, running entirely at the edge, eliminating the performance barriers of traditional cloud deployments.
Agent Capabilities
Build and deploy AI agents using models that support Tool Calling and Agentic RAG via vector search. AI Inference fully supports the LangGraph framework from LangChain, providing end-to-end tooling for building, monitoring, and evaluating complex AI agents. These agents can automate processes, create assistants, and implement advanced RAG architectures, all running closer to the user for optimal performance.
Integration with Edge SQL
AI Inference works with SQL Database for data capabilities:
- SQL Database with Vector support enables semantic queries at the edge of the network.
- Hybrid Search combines full-text and vector search for more precise, contextually relevant results.
- Efficient RAG implementations that leverage both textual and semantic information.
This integration creates a comprehensive platform for building responsive, intelligent applications that operate where your users are.
Industry-Standard Compatibility
Our AI Inference offering supports integration with:
- OpenAI-compatible API interfaces, allowing easy migration of existing applications.
- LangChain/LangGraph frameworks.
This support ensures you can leverage your existing knowledge and tools while gaining the performance benefits of edge deployment. Read more in the product reference documentation.
What’s Next
We’ve created a platform that enables cost-effective, truly responsive, efficient, and scalable AI applications, addressing the core limitations of cloud-based approaches.
Ready to experience the edge advantage? Talk with our experts today!. We are here to help you on your AI journey.
