You will get I will build a custom SDXL synthetic human generation pipeline
Project details
This project is designed for teams that want to move beyond one-off AI image generation and build a structured synthetic human workflow using SDXL.
Instead of relying on isolated prompts, I help set up a reproducible generation pipeline where datasets, identity consistency, and generation runs are organized inside a usable workflow structure.
The goal is not just to generate images, but to create a system that allows the same synthetic character to be reused across scenes, concepts, and campaign variations with predictable output behavior.
This type of setup is useful for agencies building synthetic model pipelines, teams testing virtual character workflows, and founders preparing demonstration environments around generative image systems.
The result is a structured SDXL workflow that can be operated, tested, and extended after delivery instead of a temporary prototype that stops working outside a demo session.
Instead of relying on isolated prompts, I help set up a reproducible generation pipeline where datasets, identity consistency, and generation runs are organized inside a usable workflow structure.
The goal is not just to generate images, but to create a system that allows the same synthetic character to be reused across scenes, concepts, and campaign variations with predictable output behavior.
This type of setup is useful for agencies building synthetic model pipelines, teams testing virtual character workflows, and founders preparing demonstration environments around generative image systems.
The result is a structured SDXL workflow that can be operated, tested, and extended after delivery instead of a temporary prototype that stops working outside a demo session.
AI Algorithms
Convolutional Neural Network, CycleGAN, Generative Adversarial Network, Transformer Model, Variational AutoencoderAI Applications
AI Text-to-Image, AI-Generated Art, Facial Recognition, Image Analysis, Image Processing, Image Recognition, Image-to-Image Translation, Neural Style Transfer, Synthetic Data GenerationAI Development Language
PythonAI Tools
Gradio, Hugging Face, NVIDIA AI Platform, PyTorch, Streamlit, TensorFlowAI Models
DALL-E, GPT-4, LLaMA, Midjourney AI, Stable DiffusionWhat's included
| Service Tiers |
Starter
$600
|
Standard
$1,200
|
Advanced
$3,000
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | |||
Batch Normalization | - | - | - |
Database Integration | - | - | - |
Detailed Code Comments | - | ||
Image Upscaling | - | - | - |
MLOps | - | - | |
Model Deployment | - | ||
Model Documentation | - | ||
Model Monitoring | - | - | - |
Model Testing & Optimization | - | ||
Model Tuning | - | - | |
Natural Language Processing | - | - | - |
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | |||
Setup File | |||
Source Code | - |
Optional add-ons
You can add these on the next page.
Identity consistency testing outputs
(+ 1 Day)
+$150
Dataset preparation review
(+ 2 Days)
+$200
LoRA training workflow guidance
(+ 2 Days)
+$350Frequently asked questions
About Stan
SDXL LoRA Engineer | Synthetic Humans | Identity Consistency Pipelines
Aadorp, Netherlands - 1:12 pm local time
Most AI image workflows can create impressive one-off visuals.
The harder problem is generating the same synthetic person reliably across different scenes, outfits, lighting conditions, camera angles, and campaign concepts.
That is the gap I focus on.
I help agencies, visual production teams, and AI media companies build reproducible systems for synthetic human generation. My work is not focused on random prompt experiments or generic AI automation. I build structured pipelines that can be trained, tested, repeated, and extended.
Typical systems I work on include:
• SDXL-based image generation workflows
• LoRA training pipelines for synthetic identities
• dataset preparation and captioning structures
• identity-consistency workflows across multiple outputs
• character persistence across scenes and campaigns
• realism-focused generation pipelines
• inference workflows for repeatable production output
• internal demo environments for testing generated results
My focus is turning a visual AI concept into a usable production workflow.
That usually means helping a team move from “we can generate nice images sometimes” to “we can generate this specific person, in this specific style, across many usable variations.”
I have built and tested private end-to-end systems where datasets are prepared, models are trained, generations are triggered, and outputs are reviewed inside a structured workspace environment. This includes work around synthetic human consistency, campaign-style generation, and reusable identity workflows.
I am usually a strong fit for:
• AI agencies building synthetic model or virtual influencer pipelines
• visual studios that need repeatable character generation
• marketing teams using generative humans in campaigns
• founders building AI image products
• teams that need SDXL / LoRA workflow structure
• companies moving beyond Midjourney-style one-off prompting
I am not the right fit for generic ChatGPT automation, Zapier workflows, basic prompt writing, or no-code AI tasks.
My value is in the technical layer behind the output: dataset structure, LoRA training logic, generation workflow design, identity stability, and production-ready execution.
If you need a custom generative pipeline that can create consistent synthetic humans instead of random one-off images, I can help you build it.
Steps for completing your project
After purchasing the project, send requirements so Stan can start the project.
Delivery time starts when Stan receives requirements from you.
Stan works on your project following the steps below.
Revisions may occur after the delivery date.
Review goals and dataset availability
Define intended synthetic human workflow and confirm dataset readiness or preparation needs.
SDXL workflow structure setup
Set up a reproducible generation workflow aligned with identity-consistency requirements.