Visual AI pipeline builder

Build a pipeline.
See it run.

Start with an Interface and one model. Connect them, Build, then Play. Add memory, prompts, cache, routing, and other modules as your workflow grows.

Request early access See how it works

Drag-and-drop pipelines
Local and API models
Visible execution

A simple VOIDE pipeline connecting an Interface and GPT model — A first pipeline: connect an interface to a model

Why VOIDE

AI systems should be visible.

Most AI workflows disappear inside code. VOIDE puts the complete system on a canvas so builders can understand what runs, where information goes, and why the result changed.

Compose

Place models, memory, cache, tools, prompts, interfaces, and control modules on a visual canvas.

Connect

Wire fields between modules. Connections define both data flow and execution order.

Run

Build the graph you designed, then watch every module wait, process, complete, bypass, or fail.

Improve

Change one part at a time and test whether memory, routing, verification, or another model improves the result.

How it works

Place. Connect. Run.

Start with an empty canvas. Add the modules you need, connect their ports, then build and play. The same canvas can stay simple or grow into a multi-model workflow.

01
Place modules
Drag an Interface and an LLM onto the canvas.
02
Connect the flow
Draw a wire and choose which fields to pass along.
03
Build and play
Compile the graph, run it, and follow activity on the canvas.

VOIDE Wire Options mapping user message, history, and attachments to model inputs

The canvas is the specification

What you connect is what runs.

Wires define data flow and execution order. Map the fields you need, then inspect the pipeline as it runs.

ModularInspectableProvider-flexibleRepeatable

One canvas, different workflows

Add capability when you need it.

VOIDE canvas with an Interface, Cache, prompt modules, and two connected language models — **A working multi-model canvas**Combine models, prompts, and cache in one visible flow.

VOIDE pipeline connecting an Interface, Memory, Llama model, and Log — **Bring memory into the flow**Connect retrieval and saving alongside a model.

VOIDE canvas with a Switch routing between model outputs and logging — **Build alternate paths**Use a Switch module to route a pipeline through separate outputs.

Build experimentsCompare models, memory designs, prompts, routing strategies, and multi-model workflows.

Understand failuresSee which module ran, what route activated, and where the pipeline stopped.

Keep controlUse local models, API models, or both without redesigning the entire workflow.

VOIDE canvas showing Gemini, GPT, prompts, Cache, and Log modules connected in a multi-model pipeline — **Grow from one model to a complete system.** Expand a simple connection into a multi-model workflow with prompts, shared cache, and logging.

Early access

Would you use VOIDE?

VOIDE is under active development. I’m looking for AI builders, developers, researchers, and curious early users willing to try it and give direct feedback about what is useful, confusing, or missing.

prodieseltech@gmail.com