Data Activation · A model-agnostic AI video pipeline built for scale
Personalized video at scale, with a fallback model so quality holds if a provider fails.
A model-agnostic pipeline is our alternative to betting a product on a single AI provider.
The business challenge
Generating personalized video at scale meant depending on a single AI model that could break, change pricing, or produce flawed output overnight. The program needed reliable, consistent video quality without being locked to one provider.
What we built
We built the video pipeline to be model-agnostic, with a primary provider and a fallback, so quality holds as the AI landscape shifts. It supports per-segment regeneration and a negative-prompt guardrail library to keep output on-brand and appropriate, and generation is scoped to the primary user for privacy. The result is a production pipeline that stays dependable no matter what happens upstream.
- Never locked to one model
- Quality holds as providers change
- On-brand output by design
- Built to regenerate, segment by segment
- Model-agnostic video architecture
- Primary and fallback providers
- Per-segment regeneration
- Negative-prompt guardrails
- Review step
Connected sources
One architecture · your data stays yours
It’s just 3 steps
- Capability
- Data Activation
- Solution
- AI video pipeline
- Build
- Custom, not off the shelf
- Data
- Generation scoped to the primary user
- Data ownership
- The client
- Status
- In Production
