AIMA — AI Inference Managed by AI

Why We Built AIMA

Deploying an AI model shouldn't require three days of research and a week of troubleshooting.

Today, getting a model to run means: checking hardware compatibility, selecting inference engines, tuning VRAM allocation, writing Docker configurations, resolving driver conflicts... Every time you switch machines, you start from scratch. This process prevents AI from moving from the lab to real production environments.

AIMA's answer: Let AI manage AI inference itself. You only need to tell it "run this model," and everything else—hardware detection, engine selection, configuration optimization, container orchestration—is handled automatically.

Product Positioning

AIMA is an AI inference infrastructure automation platform for teams that need to deploy and manage AI models quickly across heterogeneous hardware.

• For AI Engineers: Say goodbye to manual configuration and focus on the models themselves
• For Operations Teams: One binary manages all devices, unified control from single machines to clusters
• For Enterprise Decision Makers: Make full use of existing hardware assets, treating domestic and international chips equally

Core Values

Plug-and-Play

One Go binary, zero dependencies. Run it on any machine, and it automatically discovers GPUs (NVIDIA, AMD, Huawei Ascend, Hygon DCU, Apple Silicon), identifies optimal configurations, and deploys inference engines. No need to understand CUDA versions, no need to write Dockerfiles.

Knowledge-Driven, Not Code-Driven

Traditional solutions write specialized adapter code for each engine and hardware type. AIMA replaces these code branches with a YAML knowledge base—adding new hardware or engines only requires adding a description file, not changing code. This allows the system to quickly keep pace with the explosive growth of AI hardware.

Let AI Agents Take Control

AIMA exposes 56 MCP tool interfaces, allowing AI Agents to fully control hardware, models, engines, deployments, and clusters just like human operators. This isn't just automation—it's teaching machines to perform autonomous operations.

Offline-First, From Edge to Datacenter

All core functions have zero network dependencies. Whether it's edge devices on factory floors or government/enterprise data centers without external internet access, AIMA works completely. Network is an enhancement, not a prerequisite.

Verified Hardware Ecosystem