You will get Build an AI MVP with Flask + Replicate
Project details
I will build a fully working AI MVP using Flask and Replicate. You will get a backend API, a simple web UI, and complete setup files so you can run it on your own server. The project covers model integration (e.g., Stable Diffusion, restoration, image-to-video), UI/UX for testing inputs, and deployment guidance on AWS EC2 with Gunicorn + Nginx. My focus is on delivering a functional prototype quickly, with clean code, documentation, and support so you can validate your idea fast.
AI Algorithms
Autoencoder, Convolutional Neural Network, Generative Adversarial Network, Large Language Model, Multimodal Large Language Model, StyleGAN, Transformer Model, Variational AutoencoderAI Applications
AI Chatbot, AI Text-to-Image, AI-Generated Art, AI-Generated Video, Image Analysis, Image Processing, Image Recognition, Image Upscaling, Image-to-Image Translation, Object DetectionAI Development Language
PythonAI Tools
Hugging Face, PyTorch, TensorFlowAI Models
BERT, LLaMA, Stable DiffusionWhat's included
| Service Tiers |
Starter
$180
|
Standard
$300
|
Advanced
$600
|
|---|---|---|---|
| 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.
Fast Delivery
+$60 - $300
Additional Revision
+$30
+1 Model Integration
(+ 1 Day)
+$80
Extended support (14 days)
+$70
+1 API endpoint
+$50Frequently asked questions
About Muhmmed Mesut
Generative AI Engineer | ComfyUI Workflows, Custom Nodes & Multimodal
Mersin, Turkey - 7:01 am local time
I am a Generative AI Engineer focused on building robust, scalable, and controllable AI pipelines.
My approach combines creative vision with a deep technical understanding of Python and Deep Learning components (GANs, CLIP, VAE, U-Net, Schedulers, Samplers, and LDMs). I don't just connect nodes in ComfyUI; I understand the mathematical logic behind them—allowing me to engineer precise solutions, debug complex errors, and optimize workflows for maximum efficiency.
My Core Services:
Advanced ComfyUI Automation: Building custom .json workflows for consistent character generation (Flux + PuLID), product placement, and video processing.
Custom Node & Python Integration: Developing custom scripts to extend ComfyUI functionalities or integrating workflows into your local/cloud infrastructure (RunPod).
Model Development & R&D: Background in researching and implementing diffusion models (LDM, UNet, Samplers) and fine-tuning LLMs (Mistral 7B).
Workflow Optimization: Troubleshooting technical issues, reducing generation times, and solving VAE/Tensor mismatches.
Technical Stack:
Frameworks: ComfyUI, PyTorch, Python.
Models: Flux.1, SDXL, Stable Diffusion 1.5, Mistral (LLM).
Tools: ControlNet, IP-Adapter, LoRA Training, RunPod/Cloud Deployment.
Whether you need a complex automated pipeline for your agency or a technical fix for your existing workflow, I provide engineering-grade solutions.
Check my portfolio below to see the logic behind the visuals.
Steps for completing your project
After purchasing the project, send requirements so Muhmmed Mesut can start the project.
Delivery time starts when Muhmmed Mesut receives requirements from you.
Muhmmed Mesut works on your project following the steps below.
Revisions may occur after the delivery date.
Setup & Requirements
Review client request, set up environment, confirm model availability.
Model Integration
Integrate selected model with Flask API and configure parameters.