You will get a LLM Gateway / RAG
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Project details
A RAG system using Amazon Web Services with Amazon Bedrock gateway, vector search, and model routing enables efficient, context-aware AI responses. Data is converted into embeddings and stored in a vector database (e.g., OpenSearch) for semantic retrieval.
When a query is received, the Bedrock gateway retrieves relevant context using vector search and combines it with the prompt. A routing layer then selects the most suitable foundation model based on task type, cost, and performance. The chosen model generates a grounded response using both retrieved data and the user query.
This architecture reduces hallucinations, improves accuracy, supports multiple models, and ensures scalable and optimized AI response generation for enterprise applications.
When a query is received, the Bedrock gateway retrieves relevant context using vector search and combines it with the prompt. A routing layer then selects the most suitable foundation model based on task type, cost, and performance. The chosen model generates a grounded response using both retrieved data and the user query.
This architecture reduces hallucinations, improves accuracy, supports multiple models, and ensures scalable and optimized AI response generation for enterprise applications.
Programming Languages
HTML & CSS, Python, JavaCoding Expertise
Cross Browser & Device Compatibility, Performance Optimization, SecurityWhat's included $1,800
These options are included with the project scope.
$1,800
- Delivery Time 6 days
- Number of Revisions Unlimited
- Design Customization
- Content Upload
- Responsive Design
- Source Code
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HS
Hannah S.
Feb 5, 2026
Laravel Project Deployment
RM
Ravi M.
Apr 22, 2024
Full Stack Developer
About Ammar
AI & Full-Stack Developer | SaaS MVPs, Web Apps | AWS
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Gujranwala, Pakistan - 12:23 am local time
I'm an AI & Full-Stack Developer specializing in building scalable SaaS products, AI-powered applications, and modern web solutions that help businesses automate processes and grow faster. I work across the entire development lifecycle—from planning and architecture to development, deployment, and ongoing optimization.
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RAG System with Bedrock Gateway, Vector Search and Model Routing Setup