Tired of paying hundreds for Higgsfield, Kling, Seedance… or just want more control over your process and better creative freedom? Entering the world of Stable Diffusion is not the easiest task. Especially if you’re chasing 100% consistency of characters across scenes and you need to train your own LoRAs. That’s where LoRA Pilot comes in. LoRA Pilot is an open-source, “batteries-included” stack that helps you go from dataset → trained LoRA → testing → generating without spending days fighting installs, CUDA weirdness, and broken dependencies. It bundles the tools people already use (kohya_ss / diffusion-pipe for training, ComfyUI for testing, InvokeAI for inference) into a more guided workflow you can run on RunPod or locally. What you get in practice: - Train your own character LoRAs for consistent faces/outfits/styles - Test fast (ComfyUI) and iterate without rebuilding your entire setup - More control than “black box” SaaS tools, at a fraction of the cost - Open-source, so you can actually understand and customize your pipeline If you’re serious about repeatable creative output (ads, shorts, brand characters, client work), custom LoRAs are the unlock. LoRA Pilot is my attempt to make that unlock accessible without needing to become an AI engineer. GitHub: https://github.com/vavo/lora-pilot Website: https://www.lorapilot.com If you’re in this group and you’ve tried Stable Diffusion before: what was your biggest blocker, setup, dataset prep, training settings, or testing/iteration?