Vivek isn't taking new orders for this project right now. Here are some similar projects to explore.
You will get an End-to-End RAG (Retrieval-Augmented Generation) Application
Project details
I help businesses and professionals unlock the power of their own data by building end-to-end Retrieval-Augmented Generation (RAG) applications. Unlike generic AI chatbots, a RAG system ensures responses are grounded in your documents, delivering accuracy, reliability, and trust.
What sets me apart is my ability to go beyond just connecting an LLM—I design the entire pipeline: data ingestion, preprocessing, vector database integration, embeddings, model retrieval, and deployment. I can either work with your preferred tools or recommend the most efficient, cost-effective stack tailored to your project.
With 3+ years of hands-on experience in NLP, Generative AI, and cloud-native ML deployment, I’ve built production-ready AI content detectors, smart assistance platforms, and scalable pipelines. My focus is not only on technical performance but also on business value, ensuring the solution is usable, maintainable, and future-proof.
Whether you need a knowledge assistant, research bot, or enterprise-grade AI search tool, I’ll deliver a solution that is well-documented, tested, and ready to scale.
What sets me apart is my ability to go beyond just connecting an LLM—I design the entire pipeline: data ingestion, preprocessing, vector database integration, embeddings, model retrieval, and deployment. I can either work with your preferred tools or recommend the most efficient, cost-effective stack tailored to your project.
With 3+ years of hands-on experience in NLP, Generative AI, and cloud-native ML deployment, I’ve built production-ready AI content detectors, smart assistance platforms, and scalable pipelines. My focus is not only on technical performance but also on business value, ensuring the solution is usable, maintainable, and future-proof.
Whether you need a knowledge assistant, research bot, or enterprise-grade AI search tool, I’ll deliver a solution that is well-documented, tested, and ready to scale.
AI Algorithms
Large Language Model, Transformer ModelAI Applications
AI Chatbot, Conversational AI, Machine Translation, Natural Language Generation, Natural Language UnderstandingAI Development Language
PythonAI Tools
Azure OpenAI, GitHub Copilot, Gradio, Hugging Face, Microsoft 365 Copilot, NVIDIA AI Platform, PyTorch, Streamlit, TensorFlowAI Models
BERT, ChatGPT, GPT-4, LLaMAWhat's included
| Service Tiers |
Starter
$49
|
Standard
$99
|
Advanced
$149
|
|---|---|---|---|
| Delivery Time | 2 days | 5 days | 15 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 |
Frequently asked questions
4 reviews
(4)
(0)
(0)
(0)
(0)
This project doesn't have any reviews.
MM
Mohammad M.
Aug 24, 2025
30 minute consultation
MH
Muhammad Sikandar H.
Jan 20, 2023
Speech to Lip-Sync Generation
Another Great Project.
Thanks.
Thanks.
MH
Muhammad Sikandar H.
Jan 19, 2023
AI DeepFake and Lip Sync
great work.
Thanks
Thanks
MH
Muhammad Sikandar H.
Jan 18, 2023
Face Swap using deep fake or AI
Vivek is a very hard working and smart working guy, The job he did for me in a very quick time was really good.He keeps his word and it was a pleasure working with such nice guy.
Really appreciate his work ethics.
Will have more orders for him shortly.
Thanks & Keep it up.
Really appreciate his work ethics.
Will have more orders for him shortly.
Thanks & Keep it up.
About Vivek
AI Engineer | Agentic AI | LLMs & RAG | AI Automation & SaaS
Calgary, Canada - 7:33 am local time
With 5+ years of freelance experience, I specialize in building end-to-end AI applications: from intelligent chatbots and RAG pipelines to agentic AI workflows and full SaaS backends. I handle the full stack: AI architecture, backend development, and deployment.
⚡ What I Build:
• 🤖 AI Chatbots & Conversational Agents: custom LLM-powered chatbots trained on your data, integrated into websites, apps, and workflows
• 🔍 RAG & Document Intelligence: retrieval-augmented generation systems with hybrid search, knowledge graphs, and cited, grounded answers
• 🧠 Agentic AI Pipelines: multi-step reasoning agents with tool use, memory, self-correction, and human-in-the-loop escalation
• ⚙️ AI Automation: automate manual workflows with LLMs, document processing, data extraction, and intelligent decision-making
• 📊 LLM Integration & Fine-tuning: OpenAI, Claude, LLaMA, Mistral; prompt engineering, fine-tuning, and evaluation
• 🏗️ AI-Powered SaaS Backends: FastAPI, background job workers, auth, REST APIs, and cloud deployment: production-ready from day one
• 💬 NLP Systems: semantic search, entity extraction, classification, summarization, and Q&A
🛠️ Tech & Tools:
AI/LLM: OpenAI GPT-4o · Claude · LLaMA · Mistral · vLLM · LangChain · Hugging Face
Retrieval: ChromaDB · Pinecone · Neo4j · FAISS · BGE Embeddings · CrossEncoder Reranking
Backend: Python · FastAPI · Docker · PostgreSQL · SQLite · Redis
Cloud & MLOps: AWS · GCP · Docker Compose · CI/CD
Other: Computer Vision · Audio/Speech AI · Whisper · PyTorch
💡 Why Work With Me:
✅ Production-grade, not prototype: I build systems that handle real data, real load, and real edge cases
✅ Full-stack ownership: from LLM prompt to deployed API, I manage the entire lifecycle
✅ Clear communication: regular updates, plain-language explanations, no surprises
✅ Fast delivery: I keep scope tight and ship iteratively
📩 Let's build your AI system. Message me and we'll scope it out together. 🚀
Steps for completing your project
After purchasing the project, send requirements so Vivek can start the project.
Delivery time starts when Vivek receives requirements from you.
Vivek works on your project following the steps below.
Revisions may occur after the delivery date.
Plan & Setup
Gather requirements, choose the best stack, and prepare data/documents.
Build & Test
Develop the RAG pipeline (database + LLM integration), create API/UI, and test for accuracy.