You will get a powerful, all-in-one LLM-based interface
Project details
This project involves developing a customized large language model (LLM) solution that enables advanced language understanding, tailored fine-tuning, and seamless deployment for business or research needs. It includes building an inference-ready model, fine-tuning it with specialized data using LoRA, and integrating a retrieval-augmented generation (RAG) system with a vector database. The solution is designed to run efficiently on cloud platforms like AWS, GCP, or Azure, offering clients a robust, scalable, and all-in-one LLM interface tailored to enhance real-world applications.
AI Algorithms
Convolutional Neural Network, Large Language Model, Multimodal Large Language Model, Variational Autoencoder, YOLOAI Applications
AI Chatbot, AI Content Creation, AI Text-to-Image, AI Text-to-Speech, AI-Enhanced Medical Imaging, AI-Generated Art, AI-Generated Code, Conversational AI, Facial Recognition, Image Recognition, Machine Translation, Natural Language GenerationAI Development Language
PythonAI Tools
Azure OpenAI, GitHub Copilot, Hugging Face, NVIDIA AI Platform, PyTorch, Streamlit, TensorFlow, Word2vecAI Models
AlphaCode, BLOOM, ChatGPT, DALL-E, GPT-3, GPT-4, LaMDA, LLaMA, Midjourney AI, OpenAI Codex, Stable Diffusion, WhisperWhat's included
| Service Tiers |
Starter
$500
|
Standard
$1,000
|
Advanced
$3,000
|
|---|---|---|---|
| Delivery Time | 2 days | 8 days | 15 days |
Number of Revisions | 5 | 10 | 15 |
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
+$700 - $5,000
Additional Revision
+$30
Custom UI design
(+ 1 Day)
+$100
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About Anas
Expert AI Automation and AI Agentics | Expert Computer Vision | Ph.D
68%
Job Success
Nador, Morocco - 5:25 pm local time
Recent Achievements,
⚫⚪ ComfyUI & FLUX Image Generation Workflow
Enhanced a ComfyUI workflow built on FLUX to improve object generation, scene composition, and style consistency using custom LoRA models. Integrated reference-image conditioning, advanced node workflows, and animation pipelines to generate stylized image sequences suitable for short-form video content without traditional video editing tools.
Tech Stack: LoRA workflows, node-based AI systems, GPU optimization, batching, and automation, VRAM optimization, ComfyUI, FLUX, LoRA, Stable Diffusion, ControlNet, IPAdapter, AnimateDiff, Python, Custom Nodes.
⚫⚪ Real-Time AI Voice Agent
Created a low-latency AI voice assistant capable of handling customer conversations and triggering backend actions.
Tech Stack: Deepgram, ElevenLabs, OpenAI, Claude, Twilio, WebSockets, FastAPI, LangChain, Vapi, Retell, voicehub
⚫⚪ Enterprise AI Document Processing
Built an AI-powered document processing system that automatically extracts, validates, and routes information from PDFs and emails. Developed with FastAPI, LangGraph, OpenAI/Claude, Qdrant, and PostgreSQL, with human-in-the-loop validation for reliable automation.
⚫⚪ AI Agent Development
Designed and deployed intelligent AI agents capable of reasoning, tool calling, document retrieval, and workflow automation for customer support and business operations.
Tech Stack: LangGraph, LangChain, OpenAI, Claude, Gemini, Qdrant, Pinecone, PostgreSQL, FastAPI, Docker, Redis, Python.
⚫⚪ AI Workflow Automation
Built end-to-end AI automation pipelines that integrate LLMs with external services to automate repetitive business processes, CRM operations, document handling, and notifications.
Tech Stack: n8n, Zapier, Make, FastAPI, OpenAI, Claude, Gemini, Webhooks, REST APIs, PostgreSQL, Docker, Python.
⚫⚪ Custom AI Assistants & RAG Systems
Developed domain-specific AI assistants using Retrieval-Augmented Generation (RAG), LangChain, OpenAI, and Claude. Built knowledge bases with vector search to deliver accurate, context-aware responses.
⚫⚪ Computer Vision & Deep Learning
Developed computer vision solutions for object detection, segmentation, image classification, and 3D vision using PyTorch, OpenCV, YOLO, SAM, and TensorRT. Optimized models for deployment on resource-constrained devices.
🧠 TOOLS AI GEN
I'm a generative AI expert with experience in creating a wide range of high-quality AI-generated images and videos using tools like:
nano banana pro, gpt image 2 , midjourney8.2 , higgsfield Soul / cinema, photoshop, seedance 2 , kling 3.0 4k ,veo 3.1 , kling motion control , dzine , heygen ,eleven labs , topaz , and more.
🧠 Advanced AI & LLM Expertise
• AI Agents & Voice Assistants: CrewAI, AutoGen, Amazon Polly, Deepgram, Rasa AI, n8n, zapier
• Open-Source LLMs: LLaMA 3, Mistral 7B, Mixtral 8×7B, Falcon, Gemma
• LLM Fine-Tuning: PEFT, LoRA, QLoRA, RLHF, DPO using Unsloth, Axolotl, HuggingFace AutoTrain
• Prompt Engineering: Multi-turn, Few-shot, Zero-shot, RAG-based prompting
• RAG Systems: LangChain, LlamaIndex, ChromaDB, FAISS, Pinecone, Qdrant
• Quantization & Optimization: AWQ, GPTQ, GGUF, GGML, vLLM, TGI, TensorRT-LLM
• AI Deployment: AWS SageMaker, RunPod, GCP AI Platform, Vercel AI SDK
• Synthetic Dataset Generation & LLM Evaluation Frameworks
✔️ Computer vision and Robotics projects
✔️ Robotics (SLAM, motion planning)
✔️ Object detection in images
✔️ Instant segmentation
✔️ Pose body location
✔️ Classification
✔️ Text-to-image (T2I)
✔️ Image reconstruction (NeRF)
✔️ Image and video enhancement
✔️ Augmented reality
✔️ Autonomous robots
✔️ Medical imaging
✔️ Traffic Surveillance
✔️ Video analyzer (football applications, track customer)
🖥️ Backend Development
• Python, FastAPI, Flask, Django, Node.js, Express.js, Nest.js
• REST APIs, GraphQL APIs, scalable backend architectures
• Databases: PostgreSQL, MySQL, MongoDB, Firebase, Firestore
• Infrastructure & DevOps: Docker, Kubernetes, Redis, Nginx, AWS EC2, S3, Lambda
• AI Integrations: LangServe, LangSmith, HuggingFace Transformers
• Automation & Testing: Celery, Pytest, Unittest, Selenium
🌐 Frontend Development
• React.js, Next.js, Vue.js, Nuxt.js, React Native
• TypeScript, Redux Toolkit, Tailwind CSS
• Progressive Web Apps (PWA) & Single Page Applications (SPA)
• Responsive and modern UI/UX development
🛠️ Additional Technologies
• Scikit-learn, NumPy, Pandas, Matplotlib
• OpenAI APIs, Whisper, GPT integrations, AI Chatbots
• Git/GitHub, Linux (Ubuntu/CentOS), cloud-native development
💡 I focus on delivering:
✔ Scalable and production-ready AI systems
✔ High-performance LLM pipelines
✔ Clean, maintainable, and optimized code
Steps for completing your project
After purchasing the project, send requirements so Anas can start the project.
Delivery time starts when Anas receives requirements from you.
Anas works on your project following the steps below.
Revisions may occur after the delivery date.
Initial Consultation
- Understand the client’s vision, requirements, and project goals. - Detail all deliverables, timelines, and resource needs. - Propose an approach that aligns with the client’s needs. - Establish a communication plan for regular updates.
Build the Project
- Gather and prepare data for model training or fine-tuning. - Choose and configure the model according to project goals. - Build the main components of the project. - Ensure the model and infrastructure work seamlessly.