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Case study

Animatrix

The Challenge

Image generation products often struggle with slow render times, confusing controls, and inconsistent results. The objective was to provide a simple UI with sensible defaults while still enabling advanced users to fine-tune outputs.

  • Balancing quality vs latency on GPU-heavy workloads
  • Providing consistent results across varying prompts and styles
  • Designing a clean UX for both beginners and power users
  • Managing generation queues and concurrent usage reliably

Our Solution

We built Animatrix as a modern generative image workflow: prompt → generate → iterate → export. The platform supports presets, history, and project organization to help users move from experimentation to production.

  • Prompt builder with presets for common styles and use cases
  • Generation history to compare iterations and reuse settings
  • Queue-based job processing with progress feedback
  • Export-ready outputs with common aspect ratios and formats

Challenges We Overcame

  • Compute management: Optimizing GPU utilization and job scheduling
  • Quality controls: Aligning outputs with user intent through better defaults and presets
  • Performance: Keeping the UI responsive while long-running jobs execute
  • Scalability: Ensuring the system can grow with increasing demand

Technology Stack

Stable Diffusion
Python
FastAPI
React
Docker
AWS

Results & Impact

  • Faster creative iteration with a prompt → generate → refine loop
  • Clear path from experimentation to shareable/exportable visuals
  • Infrastructure foundations to scale generation workloads
  • Consistent UX for both casual users and advanced creators

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