Turn an Audio Podcast into Illustrated Audiogram Clips

AI transcribes the speech, chooses the three moments and gives each moment its title. AI also draws the art, and writes the show notes and the post captions. The audio wave and the layout come from the template.

No. The workflow runs from an audio file with no video track. The picture in each clip is AI art.

No. The recording must have speech. The workflow finds the moments from the transcript and makes the captions from the speech, so a recording with only music fails.

Yes. You write a style in the art style input, for example “Bold retro poster”. The workflow uses it in the prompt for each image, so each clip has different art in that style.

The example run on this page used 341 API credits and 13.4 AI credits. The cost of a run can change with your input, for example the length of a video or the number of rows in a spreadsheet. There is no charge for the workflow itself.

Yes. You do not have to open the app to run it. You can start it from your own code with the API, from a Zap in Zapier, or from an AI assistant that is connected to the Bannerbear MCP server. Each run takes your data and gives you the finished files.

Yes. The install gives you your own copy of the workflow and of its templates. You can change the templates, such as the colors, fonts and logo, and you can change the steps of the workflow.

A run is not instant, so the API answers at once, and the run continues in the background. Ask for the run to see its status. The status is queued, running, completed or failed. When the run is completed, it lists its outputs.

A sequence of steps that runs as one thing. Each step is an image render, an animation render, or a tool — and a step can use the output of an earlier step as its input.

Define its inputs, then supply them when you run it. Steps reference those inputs the same way they reference each other’s outputs.

POST to the workflow’s run endpoint with its inputs. The run is queued and reports progress as each step completes.

That is the point of inputs. Define the parts that change — a headline, an image URL, a name — and supply them per run.

Yes. Each run records every step, its inputs, its outputs and how long it took, so a failure points at the step that caused it rather than the whole workflow.

The run stops there and the failure is recorded against that step, with the outputs of the steps that already succeeded still available.

As long as its steps need — video work is not instant, and a workflow with several video steps takes minutes rather than seconds. Use the run’s progress or a webhook rather than holding a request open.

The workflow and its bundled templates are copied into your workspace, and the steps are rewritten to point at your copies rather than the originals.

Three on a trial. They are counted per workspace.

A workflow decides what gets made. An integration decides what triggers it and where the result goes. They are often used together.