AILocalabs tests small and local AI models on consumer hardware, publishes practical recipes, licensing notes and risks, and packages the workflows that are mature enough to ship.
> gpu.detect --local✓ NVIDIA CUDA runtime ready> mcp.connect --transport local✓ Local MCP server connected> model.run --privacy strict_Start from a workload, see commercial vs research options, then choose DIY or a packaged AILocalabs workflow.
A compact Apache-2.0 local model for tool-use experiments — with a very important warning about giving any model control of a real desktop.
A practical split between a commercial-friendly product path and a more experimental YuE2 path with model-weight licensing limits for companies.
A commercial-friendly reference route with COLMAP + gsplat, plus sparse-view and AGPL alternatives that need different licensing decisions.
A local speech stack with an Apache-2.0 model family, suitable for experiments and for packaged voice workflows when the exact artifacts and dependencies are verified.
The underlying open models are not the secret. You pay for tested defaults, Windows packaging, workflow, updates and less setup.
Offline multilingual voice synthesis
Turn text into natural speech, design new voices from descriptions, or guide style with authorized reference audio.
Private document translation for Windows
Translate private documents locally on your Windows PC. Pay once, then run local translation without per-page, credit, or token fees.
Complete songs from one sentence
Create complete songs locally from one sentence, with vocals, instrumentals, lyrics, synced LRC playback, CUDA/Vulkan acceleration, and MCP.
Local Gaussian Splat studio
Turn a single image into a fast generative 3D asset, or reconstruct a real object or space from video—all on your Windows GPU.
New focused applications for private generation, document processing, media, and agent workflows.
One local-first product ecosystemAILocalabs products use your own hardware so private files do not need to become cloud input.
Buy the product once, then run supported AI models on your own CPU/GPU without recurring token charges or an AI subscription.
Expose supported product capabilities to local agents without routing private work through a cloud service.
Keep essential generation and processing available without depending on a remote AI service.
Prompts, reference files, and generated output remain on your device by default.
Supported AILocalabs products can expose focused capabilities through local MCP, keeping tool execution close to your files and hardware.
The desktop application owns the models, GPU runtime, files, and focused workflow.
Supported products expose tools over a local connection rather than a hosted cloud endpoint.
Local agents can invoke product capabilities while execution and output stay on your machine.
Requirements vary by product, but the platform direction remains consistent: focused Windows tools, local models, local GPU acceleration, and local integration.