Back to references

Unity Framework — Parametric and Automated Animated Content Production

Design of a Unity framework and pipeline enabling rapid large-scale animated content production and testing, via a parametric and automated approach.

🧩

Client

-

Period

Jun 2024 → Feb 2025

Unity Real-time Automation Generative AI Video Production

Related domains

Production

Post-Production

Distribution

Data Analysis

Context

A production studio specializing in animated content for YouTube, targeting young audiences, faced a major constraint: quickly testing intellectual properties (IPs) in an environment where success heavily depends on the ability to iterate fast.

Traditional production methods, poorly automated and heavily dependent on offline rendering, made these tests long, expensive, and difficult to multiply.

The challenge wasn’t just producing faster, but especially drastically reducing “time to test” to evaluate an IP’s potential before investing heavily.


Challenges

  • Poorly automated animation production processes
  • Rendering and post-production times incompatible with rapid testing logic
  • Difficulty creating multiple variants of the same concept
  • Strong dependence on creative teams for repetitive tasks
  • Lack of flexibility for large-scale experimentation

Intervention

Intervention as architectural support and guidance, with the goal of designing a parametric production framework based on Unity.

My role focused on:

  • Defining the overall pipeline architecture
  • Designing parametric production principles
  • Integrating creative constraints into a technical system
  • Supporting the technical team in implementation
  • Serving as interface between creative needs and technological choices

This was a structuring and support role.


System Implemented

  • Unity framework dedicated to real-time video production
  • Parametric production: one scenario yielding multiple variants
  • Automated video exports
  • Automated post-production (video processing via ffmpeg)
  • Integration of generative AI components for audio (voices and music)
  • Pipeline designed for batch processing and rapid iteration

Results

  • Significant reduction in time-to-market
  • Major acceleration of IP time-to-test
  • Ability to produce numerous variants from the same base
  • Better allocation of creative resources to high-value tasks
  • Technical foundation ready for production use

What This Project Illustrates

  • Design of non-traditional production pipelines
  • Use of real-time engines (Unity) outside video games
  • An approach oriented toward testing, iteration, and scalability
  • An architect and facilitator role between tech and creative

Next Steps

The implemented framework is a central building block for experimenting, testing, and industrializing animated content. It paves the way for more systematic use of performance data to guide creative choices, without increasing production costs.

A similar project?

Let's discuss your needs and see how I can help.

Get in touch