Visual Builder
AskGL Studio — Visual AI Workflow Builder
See your AI pipeline before you run it. AskGL Studio is a drag-and-drop canvas where you build multi-model workflows visually — no code, no terminal. Drag blocks from the library, connect them with wires, assign a model to each block, test with real data, and save the whole thing as a reusable Blueprint.
What Is AskGL Studio?
Studio is where pipelines become visual. Instead of writing code or chaining prompts manually, you work on a canvas. Every block represents an AI operation. Every wire represents data flowing from one block to the next. Every model is assigned explicitly — you see exactly what runs where before anything executes.
The core idea
No code. No terminal. Just drag, connect, run. See your workflow — do not just imagine it. Studio shows the pipeline graph with every block, connection, and model before you run.
Drag-and-Drop Block Library
Browse the full block library and drag any block onto the canvas. Text summarizers, image generators, social copy writers, translators, code analyzers — every block is available from the sidebar.
Visual Node Connections
Connect blocks with wires to define data flow. The output of one block feeds directly into the input of the next. You see the entire pipeline graph before anything runs.
Per-Block Model Selection
Each block can use a different AI model. Assign Claude for summarization, Flux for image generation, GPT-4o for social copy — all in the same pipeline, configured visually.
Live Testing
Test your pipeline with sample input before saving. Studio runs each block in sequence and shows you the output at every stage. Debug issues before they reach production.
Save as Blueprint
When your pipeline works, save it as a reusable Blueprint. Run it again with new inputs, share it with your team, or publish it to the marketplace.
Pipeline Graph View
See your full workflow as a directed graph — every block, every connection, every model assignment — laid out visually. No guessing about what runs where.
Build a Pipeline in Studio
Walk through a real example: building a content pipeline that takes raw text, summarizes it, generates a hero image, and writes social copy — all in five steps.
Drag a Text Summary block onto the canvas
Open the block library sidebar and find the Text Summary block. Drag it to the center of the canvas. This is your entry point — it will receive the raw input and condense it.
Connect an Image Generation block
Drag an Image Generation block next to the summary block. Draw a wire from the summary output to the image input. Studio now knows that the summary feeds the image prompt.
Connect a Social Copy block
Add a Social Copy block and wire it to the summary output as well. This block runs in parallel with the image block — both receive the same summarized text.
Test with sample input
Enter a sample paragraph or paste real content into the pipeline input. Hit the Test button. Studio runs all three blocks in order, showing intermediate outputs at every node.
Save as Blueprint
When the output looks right, click Save as Blueprint. Name it, add a description, and choose whether to keep it private or publish it. Your pipeline is now a one-click workflow.
Key Capabilities
What Studio gives you that manual prompting and code-based pipelines do not.
Visual Pipeline Editing
Build AI workflows on a canvas with blocks and wires. See the full data flow before you run anything.
Model Selection Per Block
Assign a different AI model to each block. Mix Claude, GPT-4o, Gemini, Flux, and more in a single pipeline.
Live Preview and Testing
Run your pipeline with sample data and inspect output at every stage. Iterate visually before committing.
Blueprint Saving
Save finished pipelines as reusable Blueprints. Run them again with new inputs or share with your team.
Parallel and Sequential Flows
Wire blocks in sequence or in parallel. Studio handles execution order automatically based on your connections.
Full Pipeline Graph
See every block, connection, and model assignment in a single graph view. Know exactly what your pipeline does before it runs.
Studio vs. the Alternatives
Three ways to build a multi-model AI pipeline. Only one lets you see the whole thing before it runs.
Manual Prompting
Slow, error-prone, no reuseRun each model separately. Copy-paste outputs between steps. Keep track of which model does what in your head.
Code-Based Pipelines
High skill barrier, slow iterationWrite API calls, manage dependencies, handle errors in code. Requires engineering effort and maintenance.
AskGL Studio
None — full power, zero codeDrag blocks, connect wires, pick models, test live, save as Blueprint. No code, no terminal, no guesswork.
Open Studio and Build Your First Pipeline
Drag your first block, connect a wire, and test live. No code required — just your idea and a canvas.
Open Promptha