Branded Audiograms from an RSS Feed
Clean up speech by removing filler words, repeated words, long pauses, and unnecessary transcript punctuation for tighter, more polished clips.
CATAGORY
For Podcasters
INPUTS
Video / audio from upstream
INPUTS
Video / audio to downstream
What This Workflow Does
What it automates: Monitors your RSS feed, creates audiograms with full branding applied (title overlay, watermark, outro), and publishes automatically.
Who it's for: Podcast networks, branded shows, and marketing teams where consistent brand presentation on every piece of social content is required.
When to use it: Any time visual brand identity needs to appear consistently on all podcast social content.
How It Works
Step 1: RSS Feed — Detects Every New Episode
Connect your podcast RSS feed. Overlap triggers a workflow run for each new episode automatically.
Step 2: Add Audiogram — Waveform Video Created
Audio is converted to an audiogram video. Configure orientation, waveform style, and background.
Step 3: Add Title Overlay — Episode Title on Screen
An on-screen title is generated for the episode — typically the episode title or a key quote. Configure font, color, animation, and position.
Step 4: Add Watermark — Your Logo Applied
Your podcast logo or brand watermark is placed on every audiogram at your configured position and size.
Step 5: Add Outro — Branded End Card
Each audiogram closes with your branded outro — subscribe prompt, website, or show logo.
Step 6: Post to Social — Published Automatically
Fully branded audiograms are delivered to your connected social accounts.
Who's Is This For?
FAQ's
Can I vary the title overlay per episode?
Yes. The Add Title Overlay node generates a unique title for each episode using AI based on the episode content. Or write a custom prompt to control how titles are generated.
Does the branding appear consistently across every episode?
Yes. Once configured, watermark position, outro, and title style are applied identically to every audiogram the workflow produces.
Customize This Workflow
Nodes Used
