Hi, this is the AIEEV Biz & Strategy Team. When a business grows, it isn't just revenue that goes up. The number of proposals and contracts per client increases, and so does the number of quotes and delivery statements you have to draft. Checking tax invoice dates and payment status, then tracking down and resending issued files, grows right along with it. AIEEV went through the same shift as our B2B projects and Air Cloud platform business grew together. PoCs, build projects

AirCloud got a major update in June 2026. This release focused on improving the experience for every team — whether you're just getting started with AirCloud or running multiple projects every day. We redesigned the console, introduced real-time notifications, and expanded persistent volume support to cover more deployment environments. The goal was to make the platform feel faster and more intuitive at every step. For detailed usage guides, visit AirCloud Docs. This post cov

Real AI utilization starts with infrastructure — the kind that lets anyone use AI as much as they need, whenever they need it. As AI adoption accelerates, so does the infrastructure market behind it. Providers worldwide are competing across different architectures, and AIEEV is part of that race. Our approach is different: instead of building on centralized data centers, we launched as a distributed cloud that connects idle GPU resources across a decentralized network. Today,

Hi,I’m CY Lee from the DevOps/SRE team. With the launch of Air API, we’ve been building out our internal infrastructure monitoring system. Along the way, we developed an OpenClaw plugin—and in this post, I’d like to walk you through what we built and why it matters. 🙂 Before We Start If you’ve used OpenClaw for a while, you’ve probably experienced something like this at least once. The moment you try to connect an external model provider, you find yourself going through the

Across industries, job functions, and academia, more teams are building their own AI agent assistants and putting them to work. But the longer you run them, the harder it is to ignore one unavoidable reality: cost. An API invoice larger than your monthly subscription fee, quietly accumulating call by call, has become a familiar sight. AI agents don't call a model once per task. They call it tens or even hundreds of times per job -- planning, invoking tools, verifying results,

If you've ever tried serving an open-source AI model yourself, you know the pain. Setting up GPU infrastructure takes longer than choosing the model itself. Provisioning GPUs, configuring environments, scaling with traffic... the road to running a single model is way too long. Air API eliminates that entire process. It's a serverless API service for open-source AI models. No infrastructure to build. Just an API key to get started. Key Features 💡 OpenAI-Compatible Endpoint