AI FACTORY

FAQ

• Is this just a wrapper for ChatGPT?

  No. This is industrial automation. A compiled application orchestrates Kling (video), ElevenLabs (audio), and FFmpeg (assembly) into one automated workflow on your server or cloud. ChatGPT wrapping produces one output. A Factory produces thousands.
• Why do you use Rust instead of Python scripts?

  We use both. Python handles R&D and AI library integration during prototyping. Rust powers production: HD processing and 24/7 pipelines demand compiled performance, memory safety, and zero-crash reliability. We build for both stages.
• How do you ensure the content doesn’t look like generic AI spam?

  Visual Identity. We train LoRA (Low-Rank Adaptation) models specifically on your brand’s aesthetic, color palette, or mascot. This ensures your content looks proprietary and distinct from competitors using generic AI tools.
• What happens when the AI generates something outside brand scope?

  The pipeline has explicit capability boundaries. The LoRA model is constrained to your training data — it doesn’t improvise. The RAG layer grounds scripts in your source documents; where factual accuracy cannot be confirmed, the system flags for human review rather than generates unchecked output. That’s responsible engineering, not a limitation.
• Can this run alongside our existing production team?

  For high-volume work (ad variations, social updates, localizations), it automates 90–100%. For brand campaigns, it handles scripting, asset generation, and rough cuts — your team focuses on the final 10% polish. Most clients see 5–10x output without adding headcount.
• Do I own the intellectual property?

  Yes. You own the code, the pipeline, and the generated assets. We build the engine; you drive the car. You pay your own API costs (OpenAI, Kling, Replicate, RunPod) directly, so there is no middleman markup.