You will get a Production-Ready LLM App or RAG System with API Deployment
Project details
At ApexIQ, we don’t build hobby chatbots — we engineer production-ready AI systems.
If you're looking to integrate serious AI into your product, platform, or internal workflow, this project delivers everything you need to go from idea → deployment. Whether you’re a startup building an AI-powered SaaS, or a company automating knowledge access — we help you do it right.
What this project includes according to requirements:
1. LLM integration or fine-tuning (GPT-4, Claude, Mistral, LLaMA, etc.)
2. A complete RAG pipeline: document loaders, embeddings, retriever, and response engine
3. API-ready backend using FastAPI, Docker, or vLLM
4. Optional UI layer with Streamlit or Gradio
5. Clean, modular code + deployment-ready structure
6. Optional cloud deployment (Modal, Hugging Face Spaces, etc.)
7. Light logging, evaluation, and docs
We're a team of AI engineers and product builders who specialize in turning complex AI ideas into scalable tools. If you're serious about integrating AI into your stack — let’s build something that lasts.
If you're looking to integrate serious AI into your product, platform, or internal workflow, this project delivers everything you need to go from idea → deployment. Whether you’re a startup building an AI-powered SaaS, or a company automating knowledge access — we help you do it right.
What this project includes according to requirements:
1. LLM integration or fine-tuning (GPT-4, Claude, Mistral, LLaMA, etc.)
2. A complete RAG pipeline: document loaders, embeddings, retriever, and response engine
3. API-ready backend using FastAPI, Docker, or vLLM
4. Optional UI layer with Streamlit or Gradio
5. Clean, modular code + deployment-ready structure
6. Optional cloud deployment (Modal, Hugging Face Spaces, etc.)
7. Light logging, evaluation, and docs
We're a team of AI engineers and product builders who specialize in turning complex AI ideas into scalable tools. If you're serious about integrating AI into your stack — let’s build something that lasts.
AI Algorithms
Autoencoder, Feedforward Neural Network, Large Language Model, Linear Discriminant Analysis, Long Short-Term Memory Network, Multimodal Large Language Model, Recurrent Neural Network, Regression Analysis, Transformer Model, Variational AutoencoderAI Applications
AI Chatbot, AI Mobile App Development, AI Text-to-Image, AI-Generated Code, Anomaly Detection, Conversational AI, Image Processing, Image-to-Image Translation, Natural Language Generation, Speech Synthesis, Time Series Analysis, Time Series ForecastingAI Development Language
PythonAI Tools
Azure OpenAI, GitHub Copilot, Hugging Face, NVIDIA AI Platform, PyTorch, Replit, Streamlit, TensorFlow, Word2vecAI Models
AlphaCode, BERT, BLOOM, ChatGPT, GPT-3, GPT-4, LaMDA, LLaMA, Naive Bayes Classifier, OpenAI Codex, Stable Diffusion, WhisperWhat's included
| Service Tiers |
Starter
$350
|
Standard
$800
|
Advanced
$1,500
|
|---|---|---|---|
| Delivery Time | 4 days | 7 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 | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$59 - $199About SAIKUMAR
AI Agent Developer | LLM Fine-Tuning & RAG | Founder of ApexIQ.ai
Bangalore, India - 8:42 pm local time
As the founder of apexiq.ai (an AI services firm) and a YouTuber teaching AI to thousands, I bring a rare combination: deep technical expertise + the ability to communicate complex AI in business terms.
What I specialize in:
AI Agents & Agentic Systems: Custom AI agents that automate complex workflows, make decisions, and integrate with your existing tools. Built with LangChain, CrewAI, AutoGen, and custom frameworks.
LLM Fine-Tuning & Optimization: Domain-specific fine-tuning, quantization (GGUF, GPTQ, AWQ), RAG pipelines with hybrid retrieval, and prompt engineering for production accuracy.
Full-Stack MLOps on AWS: Model deployment on EKS/EC2, serverless inference with Lambda, data pipelines with EventBridge, monitoring with Prometheus/Grafana, and CI/CD for ML systems.
End-to-End Data Science: From exploratory analysis to production ML models. NLP, computer vision, time-series forecasting, recommendation systems, and predictive analytics.
Why clients choose me over other freelancers:
I don't just build models. I deploy them, monitor them, and make sure they deliver ROI. Every project includes production deployment, documentation, and a handoff that your team can actually maintain.
My background: 3+ years in data science, founder of an AI services company, active YouTuber, and deep hands-on experience with the full AWS AI/ML ecosystem.
Let's talk about your project. Send me a message with what you're building, and I'll respond within 2 hours with an honest assessment of whether I can help.
Steps for completing your project
After purchasing the project, send requirements so SAIKUMAR can start the project.
Delivery time starts when SAIKUMAR receives requirements from you.
SAIKUMAR works on your project following the steps below.
Revisions may occur after the delivery date.
Review Client Requirements
We analyze your submitted goals, use case, and data sources. If needed, we’ll schedule a quick message exchange to clarify expectations and recommend the right stack (GPT-4, LLaMA, RAG, etc.).
Plan Architecture & Tooling
We define the best-fit architecture for your project (RAG vs. LLM-only), choose tools (LangChain, LlamaIndex, Pinecone, FastAPI, vLLM, etc.), and create a modular development plan.