You will get a cloud-based LLM application deployed on AWS, Azure, or GCP
Project details
You will get a cloud-based LLM application designed, developed, and deployed on AWS, Azure, or GCP for scalability, performance, and enterprise reliability. I build secure and production-ready AI applications powered by GPT-4, Claude, Gemini, and open-source LLMs.
This includes backend setup, model integration, API orchestration, database connectivity, cloud deployment, and optimization for real-world usage. Whether you need an AI SaaS product, internal enterprise tool, chatbot platform, or AI-powered automation system, I can deliver it end-to-end.
With expertise in AWS Bedrock, Azure OpenAI, Vertex AI, and scalable AI infrastructure, I ensure your LLM app is ready for production with proper security, performance optimization, and future scalability.
This includes backend setup, model integration, API orchestration, database connectivity, cloud deployment, and optimization for real-world usage. Whether you need an AI SaaS product, internal enterprise tool, chatbot platform, or AI-powered automation system, I can deliver it end-to-end.
With expertise in AWS Bedrock, Azure OpenAI, Vertex AI, and scalable AI infrastructure, I ensure your LLM app is ready for production with proper security, performance optimization, and future scalability.
AI Algorithms
AdaBoost, Autoencoder, Convolutional Neural Network, Feedforward Neural Network, Generative Adversarial Network, Large Language Model, Linear Discriminant Analysis, Multimodal Large Language Model, Radial Basis Function Network, Recurrent Neural NetworkAI Applications
AI Chatbot, AIOps, Anomaly Detection, Facial Recognition, Machine Translation, Natural Language Generation, Natural Language Understanding, Neural Machine Translation, Neural Style Transfer, Sentiment Analysis, Speech Synthesis, Synthetic Data GenerationAI Development Language
PythonAI Tools
Adobe Firefly, Azure OpenAI, Bing AI, Copy.ai, GitHub Copilot, Hugging Face, Microsoft 365 Copilot, NVIDIA AI Platform, PyTorch, TensorFlowAI Models
AlphaCode, BERT, BLOOM, ChatGPT, DALL-E, Dolly, GPT-3, GPT-4, GPT-J, GPT-Neo, LLaMA, OpenAI CodexWhat's included
| Service Tiers |
Starter
$1,200
|
Standard
$2,400
|
Advanced
$4,000
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 10 days |
Number of Revisions | 2 | 3 | 4 |
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 | - | - | - |
About Bhupinder Singh
Agentic AI Architect | Multi-Agent Systems | RAG | LLMOps
Johnston, United States - 8:40 pm local time
With 5+ years of AI/ML experience and 30+ successful AI deployments, I specialize in building intelligent systems using LangGraph, CrewAI, AutoGen, AWS Bedrock, Azure OpenAI, and Vertex AI.
𝗠𝘆 𝗲𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲 𝗰𝗼𝘃𝗲𝗿𝘀 𝘁𝗵𝗲 𝗰𝗼𝗺𝗽𝗹𝗲𝘁𝗲 𝗔𝗜 𝗹𝗶𝗳𝗲𝗰𝘆𝗰𝗹𝗲:
✔ Multi-Agent System Design
✔ RAG (Retrieval-Augmented Generation) Pipelines
✔ MCP Server Development & Tool Integration
✔ AI Automation Workflows
✔ LLMOps, Monitoring & Evaluation
✔ AI Governance, Guardrails & Compliance
✔ Enterprise AI Infrastructure on AWS, GCP & Azure
I build AI systems that do more than just chat.
𝗥𝗲𝗰𝗲𝗻𝘁 𝘄𝗼𝗿𝗸 𝗶𝗻𝗰𝗹𝘂𝗱𝗲𝘀:
• Autonomous Loan Underwriting Agent (78% faster decisions)
• Clinical Knowledge Assistant for Hospital Chains (40K+ documents indexed)
• AI Customer Support Automation Platform ($1.2M annual savings)
• Contract Intelligence Platform (90% review time saved)
• Agentic Market Research Systems (85% analyst time saved)
𝗠𝘆 𝘁𝗲𝗰𝗵 𝘀𝘁𝗮𝗰𝗸 𝗶𝗻𝗰𝗹𝘂𝗱𝗲𝘀:
→ LangGraph, CrewAI, AutoGen
→ AWS Bedrock, SageMaker
→ Azure OpenAI
→ Vertex AI
→ Claude, GPT-4o, Gemini, Llama
→ Pinecone, Weaviate, pgvector
→ LangSmith, Arize Phoenix
→ Terraform, CI/CD, MLflow
If you're looking to build autonomous AI agents, enterprise RAG systems, or AI workflow automation, I can help you architect, build, and deploy scalable solutions end-to-end.
Steps for completing your project
After purchasing the project, send requirements so Bhupinder Singh can start the project.
Delivery time starts when Bhupinder Singh receives requirements from you.
Bhupinder Singh works on your project following the steps below.
Revisions may occur after the delivery date.
Step 1: Requirement Analysis
Understand the application use case, users, and cloud requirements
Step 2: Cloud Architecture Design
Plan infrastructure, model hosting, APIs, and integrations