You will get AI automation agents using LLMs and AWS for your business
Project details
I help businesses automate workflows and build intelligent AI agents using LLMs and AWS — from idea to production.
Most AI projects fail due to poor architecture and lack of real-world implementation. I focus on delivering production-ready AI systems that integrate with your existing tools and drive measurable outcomes.
With 9+ years of experience working across business and engineering teams, I design solutions that go beyond prototypes — including AI agents, RAG systems, and automation workflows.
Whether you want to automate operations, build a chatbot, or create a scalable AI system, I can help you define, design, and deploy the right solution.
✔ AI Agents & Workflow Automation
✔ RAG-based AI Chatbots
✔ AWS-based scalable architecture (Lambda, API Gateway, Bedrock)
✔ API & database integrations
If you're looking for someone who can take ownership from idea to execution — let’s get started.
Most AI projects fail due to poor architecture and lack of real-world implementation. I focus on delivering production-ready AI systems that integrate with your existing tools and drive measurable outcomes.
With 9+ years of experience working across business and engineering teams, I design solutions that go beyond prototypes — including AI agents, RAG systems, and automation workflows.
Whether you want to automate operations, build a chatbot, or create a scalable AI system, I can help you define, design, and deploy the right solution.
✔ AI Agents & Workflow Automation
✔ RAG-based AI Chatbots
✔ AWS-based scalable architecture (Lambda, API Gateway, Bedrock)
✔ API & database integrations
If you're looking for someone who can take ownership from idea to execution — let’s get started.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI-Generated Code, AIOps, Conversational AI, Natural Language UnderstandingAI Development Language
PythonAI Tools
GitHub Copilot, Gradio, Hugging Face, PyTorchAI Models
BERT, GPT-4, LLaMAWhat's included
| Service Tiers |
Starter
$120
|
Standard
$450
|
Advanced
$1,200
|
|---|---|---|---|
| Delivery Time | 2 days | 5 days | 10 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
About Nilesh
AWS & GenAI Solution Consultant | Build Scalable AI Systems (LLMs, RAG
Ahmedabad, India - 2:32 pm local time
Over the last 9 years, I’ve worked closely with business and engineering teams to turn complex problems into production-ready AI solutions, especially in areas like automation, analytics, and decision systems.
What I can help you with:
Build LLM-powered applications (RAG, agents, copilots)
Design scalable AWS architectures (Lambda, S3, API Gateway, Bedrock)
Convert ideas into production-ready AI systems
Automate workflows using AI → reduce cost & manual effort
Recent work:
Built a natural language → SQL system for business analytics
Developed RAG-based AI assistant for knowledge retrieval
Designed AI-driven automation workflows for operations teams
How I work:
I act as a bridge between business and engineering — leading discovery, defining architecture, and ensuring smooth execution.
If you're looking to implement AI (not just experiment) and want a consultant who can take ownership end-to-end — let’s talk.
Steps for completing your project
After purchasing the project, send requirements so Nilesh can start the project.
Delivery time starts when Nilesh receives requirements from you.
Nilesh works on your project following the steps below.
Revisions may occur after the delivery date.
#1
Requirement analysis and use-case understanding
#2
Solution design and architecture planning