You will get AI or LLM system on AWS (RAG, Bedrock, SageMaker)
Project details
This project provides a complete AI system on AWS, including RAG pipelines, LLM integration, and deployment.
I design and build AI systems using Amazon Bedrock, SageMaker, and modern data pipelines to enable applications such as intelligent chatbots, document search, and automated workflows.
The solution includes building a Retrieval-Augmented Generation (RAG) pipeline that connects your data (documents, databases, or APIs) to large language models for accurate, context-aware responses.
Data quality is critical for AI systems. Your data should be clean, structured, and ready to use. If needed, I can advise on data preparation as part of the design phase.
First, I will design the system architecture and provide a detailed plan including data flow, model selection, and expected outcomes.
After your approval, I will implement and deploy the AI system on AWS.
The system may include data ingestion, vector database integration, LLM integration, API/backend services, and basic monitoring.
This service is ideal for startups and SaaS companies building AI-powered products or automating workflows.
I design and build AI systems using Amazon Bedrock, SageMaker, and modern data pipelines to enable applications such as intelligent chatbots, document search, and automated workflows.
The solution includes building a Retrieval-Augmented Generation (RAG) pipeline that connects your data (documents, databases, or APIs) to large language models for accurate, context-aware responses.
Data quality is critical for AI systems. Your data should be clean, structured, and ready to use. If needed, I can advise on data preparation as part of the design phase.
First, I will design the system architecture and provide a detailed plan including data flow, model selection, and expected outcomes.
After your approval, I will implement and deploy the AI system on AWS.
The system may include data ingestion, vector database integration, LLM integration, API/backend services, and basic monitoring.
This service is ideal for startups and SaaS companies building AI-powered products or automating workflows.
AI Algorithms
Autoencoder, Large Language Model, Long Short-Term Memory Network, Multimodal Large Language Model, Regression Analysis, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, AI Text-to-Image, AI Text-to-Speech, AI-Generated Code, AIOps, Anomaly Detection, Conversational AI, Natural Language Generation, Sentiment AnalysisAI Development Language
PythonAI Tools
Gradio, Hugging Face, NVIDIA AI Platform, PyTorch, Streamlit, TensorFlowAI Models
BERT, ChatGPT, GPT-4, GPT-J, LLaMA, Stable Diffusion, WhisperWhat's included $2,800
These options are included with the project scope.
$2,800
- Delivery Time 14 days
- Number of Revisions 2
- AI Model Integration
- Database Integration
- Model Deployment
- Model Monitoring
- Model Testing & Optimization
- Model Tuning
- Natural Language Processing
- Prompt Engineering
- Source Code
Optional add-ons
You can add these on the next page.
Additional Revision
+$300Frequently asked questions
About Ahmad
AWS Solutions Architect | Cost Optimization, Security, AI on AWS
Chatsworth, United States - 5:01 pm local time
I help startups, SaaS companies, and development teams reduce cloud costs, strengthen security, and build scalable AWS architectures.
I’m an AWS Certified Solutions Architect and Senior Python Engineer specializing in production-ready cloud systems, serverless architectures, and AI-powered automation on AWS.
My focus is simple: secure systems, lower cloud costs, and reliable infrastructure that scales.
What I Help Clients Do
- AWS Architecture & Infrastructure
Design scalable cloud architectures and serverless systems using Lambda, API Gateway, DynamoDB, and event-driven patterns.
- AWS Cost Optimization
Identify waste, right-size infrastructure, and implement cost controls. Many environments see 20–40% cost reduction.
- AWS Security & Governance
Design secure IAM architectures, implement monitoring and guardrails, and manage multi-account AWS environments aligned with the AWS Well-Architected Framework.
- AI / LLM Systems on AWS
Build RAG pipelines and AI automation workflows using Amazon Bedrock, SageMaker, and modern data pipelines.
How I Work?
I follow a structured project approach by defining clear milestones and deliverables from the start. Large projects are broken into manageable phases to ensure transparency, steady progress, and reliable delivery.
If your AWS environment is experiencing cost drift, security gaps, scaling issues, or you’re building AI systems on AWS, feel free to reach out and discuss your project.
Steps for completing your project
After purchasing the project, send requirements so Ahmad can start the project.
Delivery time starts when Ahmad receives requirements from you.
Ahmad works on your project following the steps below.
Revisions may occur after the delivery date.
Requirements and Use Case Definition
Client shares use case, data sources, and business goals. Client is responsible for providing clean and usable data for the system.
Architecture Design and Approval
I design the AI system architecture and provide a detailed plan for review and approval.