AI generators understand prompts. Vertrum understands AI generators.
Search a niche. Get three generator-ready execution specs built from real performance data — structured for the model you're actually using.
How It Works
From search to generator-ready.
In one step.
No prompt engineering. No generator research. No iteration from zero.
Search a niche
Enter a topic, content direction, or video concept. Vertrum pulls real engagement data from top-performing content in that space.
Signal extraction
Performance data — VPS ranking, caption patterns, duration signal, hook structures — is assembled into a structured payload.
Generator-aware spec generation
A single LLM call combines your signal data with the operational rules of the generator you selected. No guessing. No generic output.
Three execution specs, ready to use
Three structured variations — different execution shapes, same signal foundation. Copy directly into your generator.
The Missing Layer
The tool making your prompt doesn't know your generator.
When you ask an LLM to write a video prompt, it produces something descriptive. It doesn't know that Kling requires an explicit motion endpoint or the generation hangs. It doesn't know that Veo needs camera instruction first or the depth engine defaults to a flat static frame.
It doesn't know what's actually performing in your niche or what hook pattern top performers are using.
It's prompting blind.
Generator-unaware. Signal-unaware. Vertrum is the layer that sits upstream.
Standard LLM Prompt
"Cinematic video of an antique typewriter restoration, satisfying before and after, dramatic transformation, smooth camera movement, hyper-realistic detail, 4k quality, viral content style..."
↓ Vertrum adds the layer above
Vertrum Execution Spec
"Extreme close-up — aged typebar mechanism... restorer's hands enter frame... rack focus as grime lifts... avoid: warped key geometry, floating hands..."
Live Example
Here's what Vertrum actually produces.
And what produced it.
Antique typewriter restoration niche, Kling 2.6 Pro. Real signal, real structure, ready to paste.
Generator-Ready Prompt
Extreme close-up — aged typewriter key mechanism, decades of grime packed into the key wells and typebars. A restorer's hands enter frame, soft brass brush moving methodically across each key. Camera holds tight on a single typebar as grime lifts and the engraved letter emerges. Slow rack focus to adjacent keys — each one transforming in sequence. Warm workshop light rakes across the chrome accents, catching the restored finish. Motion resolves as restorer lifts brush and steps back — full keyboard revealed, clean. Cinematic depth of field, hyper-realistic texture detail, natural motion. Avoid: warped key geometry, floating hands, dead background.
What Built It
VPS Range
6.1x – 24.3x
Duration Range
10–16s
Performance Ceiling
24.3xx
Signal Quality
Strong Signal
Top Performing Caption
"Found this at a garage sale for $8. 3 hours later 🤯"
Generator-Native. Model-Specific.
Kling and Veo are not the same generator.
Vertrum knows the difference.
Kling and Veo are the two leading AI video generators. Select one and watch the operational constraints update — this is what Vertrum encodes into every spec before the LLM call fires.
Kling 2.6 Pro — Operational Constraints
Element Ceiling
6
max simultaneous elements
Complexity
Medium
complexity rating
Generator
KLING
native syntax applied
Best for: Balanced quality, realistic motion, dynamic scenes
—Motion endpoint required — open-ended motion causes generation hang
—Subject defined in first 10 words — locks model focus before atmospherics
—Physics and secondary motion explicitly instructed — prevents floating limbs
These constraints are encoded into every spec Vertrum generates for this model. The LLM never guesses them.
Real Performance Signal
Not what an LLM assumes is performing.
What's actually performing.
Every spec is grounded in scraped engagement data from real content in your niche. That signal feeds the spec as instruction — not inspiration.
VPS Ranking
Content ranked by views-per-subscriber — the signal that separates viral from volume, independent of account size.
Caption Intelligence
Hook patterns, structural types, and top-performing captions from your niche. Derived from real transcripts where available.
Duration Signal
What length actually holds attention in your niche. Not assumed — pulled from the top-performing content in the dataset.
Confidence Rating
Every spec carries a signal quality score. Thin data produces honest sparse specs. Rich data produces detailed output. Never inflated.
Every Spec Includes
Three variations per search.
Each one complete.
Different execution shapes, same signal foundation. Pick the one that fits where you're going.
Generator-Native Prompt
Copy directly into your generator. Formatted for the model you selected.
Execution Shape Summary
Why the spec is structured the way it is — opening logic, progression, payoff.
Hook Intelligence
The opening moment and hook type, derived from real transcript opening lines where available.
Signal Summary
The data that informed the spec — VPS range, duration range, top caption, niche benchmark.
Failure Risk Panel
Quality concerns surface here with plain language recommendations. Honest output — not hidden.
Confidence Indicator
Signal quality visible on every spec. Strong, moderate, or thin — always shown, never inflated.
Built around the blueprint
of AI video generators.
Start from real signal. Generate with confidence.