Local-first by default
Run Ollama, llama.cpp, and local models on your hardware before ever touching a paid API. Escalate only when the job genuinely needs it — not as the only path forward.
Local-first AI harness • agent cockpit • workflow engine
A local command center for models, agents, and workflows — designed to run on your hardware by default and reach for APIs only when the job calls for it. Yours to control, yours to build on.
cadela boot --mode local-first
> loading agents: code, media, docs, review
> model router: ollama + deepseek + api fallback
> workflows: comfyui, ue5, prompts, files
> clean-room docs: enabled
> status: ready to conquer
What Cadela is
Cadela is being built as the connective layer between local LLMs, API models, ComfyUI pipelines, Unreal Engine tooling, code agents, documentation workflows, and project-specific skills — one workspace that puts you in control instead of locking you into a cloud dashboard.
The philosophy
Most AI platforms route everything through their cloud — your context, your files, your prompts — as the only option. Cadela flips that. Local models run on your workstation with zero data leakage and no per-token cost for daily work.
External APIs become a deliberate choice rather than the default. You decide what's sensitive enough to keep local and what's worth sending upstream. Your workflow, your hardware, your call.
Private by default. Powerful when you need it.
Run Ollama, llama.cpp, and local models on your hardware before ever touching a paid API. Escalate only when the job genuinely needs it — not as the only path forward.
Dedicated roles for planning, coding, reviewing, clean-room documentation, workflow generation, prompt building, and media direction — coordinated from one harness instead of a dozen tabs.
Game dev pipelines with UE5, AI media production through ComfyUI, clean-room source analysis, community bots, and prompt cookbooks — the harness bends to the project, not the other way.
Model routing
Cadela's long-term goal is to route work between local models and external APIs based on cost, privacy, speed, context size, and task type — automatically or by explicit choice.
Dive into the architecture →Get involved
Cadela is being developed openly. Follow the build log, join the conversation, or contribute.