High-Performance. Self-Hosted. Zero Setup.
A lightweight .NET middleware providing a monitored, shared foundation for local AI applications.
Overview │ Installation Guide │ Technical Data Sheet
InstantAIGate is an enterprise-grade infrastructure building block (middleware) designed for teams who need to move beyond fragile desktop AI tools (like Ollama or LM Studio) and deploy a highly-concurrent, production-ready server environment.
Built entirely in .NET, it provides an isolated server-side runtime, a built-in administration dashboard, and a seamless OpenAI-compatible API bridge. InstantAIGate firmly returns total architectural control over LLM and Embedding inference back into the hands of your infrastructure and security teams, ensuring predictable performance and strict resource management.
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🛡️ Validated Stability (LTS-First Approach) We reject the chaos of the AI hype cycle. InstantAIGate guarantees production reliability by supporting a strictly curated, regression-tested matrix of
llama.cppversions and model weights. Plan your enterprise infrastructure updates with predictability, free from sudden breaking changes or dependency conflicts. -
🔌 Drop-In OpenAI Compatibility Exposes a standardized API fully compatible with the OpenAI specification. Seamlessly route existing application workflows (including LangChain or Dify agents) to your local models by simply updating the
base_url. -
📈 Zero-Config Observability No complex metric stacks required for day-one operations. The built-in web interface provides immediate visibility into multi-GPU health, exact VRAM allocation, and real-time request queues via SignalR streams.
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⚙️ High-Density Hardware Control Extract absolute maximum throughput from a single bare-metal server. Explicitly map LLM computational layers between GPU and CPU, and enforce physical memory locking (
mlock) to guarantee zero system swap latency spikes and prevent Out-Of-Memory (OOM) crashes under heavy load. -
🔄 Dynamic Weight Pooling & Hot-Swap Manage highly concurrent workflows across your team. Host embedding models (like BGE-M3) and conversational layers (like Qwen) simultaneously. Hot-swap multi-gigabyte models on the fly via REST API or the Web UI without dropping active client connections.
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📦 Zero Python Dependency (.NET Native) Built purely in modern C# and compiled as a standalone binary. Bypass complex virtual environments, dependency hell, and Python runtime overhead. Enjoy predictable, bulletproof deployment across both Windows and Linux servers.
InstantAIGate is built on Domain-Driven Design (DDD) principles, cleanly separating core business logic from infrastructural details. This architecture ensures modularity, testability, and high native performance.
The core interaction identifier is the RepoId (e.g., "Qwen/Qwen2.5-7B-Instruct-GGUF"). The presentation layer and external APIs remain entirely agnostic of physical disk paths, file extensions, or underlying C++ bindings, ensuring a clean, abstraction-first approach to model management.
InstantAIGate is built using modern, robust technologies on both the backend and frontend:
- LLM Engine: llama.cpp (Native integration and drivers for high-performance GGUF inference)
- Backend: Modern .NET, ASP.NET Core, OpenAI .NET Client, SharpCompress (for on-the-fly native library extraction)
- Frontend: Vanilla JS, Bootstrap Icons, SignalR
⚖️ View Third-Party License Information
This project complies with all open-source licenses of its dependencies. Major dependencies, including llama.cpp, use permissive licenses such as MIT and Apache 2.0.
For the full, detailed list of third-party components, verification sources, and copyright notices, please refer to our dedicated THIRD-PARTY-NOTICES.md file.
Copyright (c) 2026 Instancium™ (https://instancium.com). All rights reserved.
This project is licensed under the Apache License 2.0 - see the LICENSE file for details.
The InstantAIGate name, logos, and all branding assets located in any media directories are not covered by the Apache 2.0 license.
Instead, all branding materials and logos throughout the project are licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0).
You are welcome to use the logo to refer to this project, but you may not modify it or use it for commercial purposes or in a way that implies official endorsement without explicit permission.