Scaling Synthetic Video Generation Without Cloud Bottlenecks
Case studyAutomotive

Scaling Synthetic Video Generation Without Cloud Bottlenecks

The challenge

An automaker needed massive synthetic video generation for simulations—but cloud costs were exploding, and rendering was too slow for agile development.

Key Obstacles

  • High cloud costs: Expensive GPU instances drained budgets
  • Slow rendering: Delays stretched development timelines
  • No scalability: Cloud-dependent workflows couldn’t keep up

Our solution

Liquid built a lightweight, local synthetic video model that ran directly on automotive hardware, eliminating cloud dependency.

The results

Faster, cheaper simulations at scale—no cloud needed.

  • 2x faster rendering speeds
  • 70% lower cloud costs
  • Scaled synthetic data production in-house
  • Gained competitive edge vs. cloud-reliant rivals