You will get a full AI data pipeline from ingestion to deployment
Project details
You will get a complete AI data pipeline built from raw data ingestion to model deployment, optimized for scalability, automation, and production performance. I design end-to-end AI pipelines covering ETL, preprocessing, embeddings, vector storage, model orchestration, and deployment workflows.
This includes batch and real-time ingestion, data transformation, feature engineering, vector database setup, AI model integration, and deployment pipelines for enterprise-grade systems. Whether you are building RAG applications, analytics systems, AI assistants, or machine learning platforms, I can create the full infrastructure.
With expertise in Kafka, AWS Glue, Spark, Snowflake, Pinecone, and cloud-native AI pipelines, I deliver robust systems that handle large-scale data efficiently and reliably.
This includes batch and real-time ingestion, data transformation, feature engineering, vector database setup, AI model integration, and deployment pipelines for enterprise-grade systems. Whether you are building RAG applications, analytics systems, AI assistants, or machine learning platforms, I can create the full infrastructure.
With expertise in Kafka, AWS Glue, Spark, Snowflake, Pinecone, and cloud-native AI pipelines, I deliver robust systems that handle large-scale data efficiently and reliably.
AI Algorithms
AdaBoost, Convolutional Neural Network, Feedforward Neural Network, Generative Adversarial Network, Long Short-Term Memory Network, Radial Basis Function Network, Recurrent Neural Network, Restricted Boltzmann Machine, Transformer Model, YOLOAI Applications
AI Chatbot, AI Mobile App Development, AIOps, Conversational AI, Facial Recognition, Machine Translation, Natural Language Generation, Natural Language Understanding, Neural Machine Translation, Neural Style Transfer, Object Detection, Sequence ModelingAI Development Language
PythonAI Tools
Adobe Firefly, Bing AI, Copy.ai, Hugging Face, Jasper AI, Microsoft 365 Copilot, NVIDIA AI Platform, PyTorch, Streamlit, TensorFlowAI Models
BERT, BLOOM, ChatGPT, Dolly, GPT-3, GPT-4, GPT-Neo, LaMDA, LLaMA, Midjourney AI, OpenAI Codex, WhisperWhat'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 | 5 |
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 - 2:04 am 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: Data Source Analysis
Review your data sources, formats, and AI workflow requirements
Step 2: Pipeline Architecture Design
Design ingestion, processing, storage, and deployment workflows