You will get RAG System & Semantic Search Optimization
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Project details
I develop AI-powered RAG (Retrieval-Augmented Generation) systems integrated with Redis semantic caching to deliver fast, accurate, and scalable data retrieval solutions. The platform can handle large datasets, provide intelligent query responses, and optimize performance through advanced caching strategies. My work includes designing the AI pipeline, integrating APIs, setting up Redis caches, and optionally creating a dashboard for managing queries and datasets. I ensure secure, maintainable code with a focus on high performance, user-friendly operation, and seamless integration with existing systems. This solution is ideal for businesses or applications that require AI-driven search, knowledge retrieval, or real-time insights from large volumes of data.
Programming Languages
JavaScript, Python, TypeScriptCoding Expertise
Cross Browser & Device Compatibility, Performance Optimization, SecurityWhat's included
| Service Tiers |
Starter
$1,000
|
Standard
$3,500
|
Advanced
$7,000
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 15 days |
Number of Revisions | 2 | 4 | 6 |
Number of Pages | 1 | 3 | 5 |
Design Customization | - | ||
Content Upload | - | ||
Responsive Design | - | - | |
Source Code |
Frequently asked questions
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Tara B.
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Temurjon came into the project mid-way. He was able to onboard fast and keep the project moving when without him it would have delayed. He brought good solutions to the unique challenges and spent time understanding the project. His availability to work on the project was greatly appreciated. I would hire Temurjon again for any of my software solutions projects.
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About Temurjon
AI Expert | Full Stack Developer | AI Integration, RAG, AI Agents
100%
Job Success
Sachse, United States - 1:40 pm local time
I help SaaS, healthcare, fintech, and automation teams build production-ready AI and full-stack systems.
Best fit: AI integrations, RAG systems, internal agents, document processing, backend automation, scalable SaaS architecture, and technical rescue work.
I work well with clients who need reliable backend design, clean data flow, secure APIs, cloud deployment, and long-term maintainability.
Core areas:
- AI, LLM, RAG, agents, chatbot workflows, document processing, and semantic search
- React, Next.js, Angular, TypeScript
- Node.js, NestJS, Python, FastAPI, Django
- PostgreSQL, MongoDB, Redis, Prisma, Elasticsearch/OpenSearch
- AWS, Docker, Kubernetes, Terraform, CI/CD
- Healthcare SaaS platforms involving EMR/EHR, patient portals, billing workflows, and clinical documentation systems
- FinTech, bill pay, banking, payment workflows, and multi-tenant SaaS platforms
- SaaS refactoring, backend performance, architecture cleanup, and technical rescue work
Relevant experience includes:
- Healthcare platforms involving EMR/EHR, patient portals, billing, inventory, and clinical workflow automation
- AI-powered clinical documentation and voice-to-text workflows
- AI dental application using Next.js, NestJS, FastAPI, PostgreSQL, and LLM integrations
- AI-powered property management SaaS with workflow automation and document processing
- FinTech and bill pay architecture for multi-tenant platforms
- AWS Lambda and ETL pipeline optimization
- Redis Oplog and Meteor performance optimization
- Document processing AI agents and RAG-based workflows
I think like an architect, but I still write code. I care about clean architecture, security, testing, failure handling, and simple communication.
I do not build fragile demos. I build systems that can survive real users and be maintained after launch.
If your project needs a senior engineer who can understand the product, identify technical risk, and ship reliable software, I can help.
Steps for completing your project
After purchasing the project, send requirements so Temurjon can start the project.
Delivery time starts when Temurjon receives requirements from you.
Temurjon works on your project following the steps below.
Revisions may occur after the delivery date.
AI-Powered RAG & Semantic Cache with Redis Integration
Develop a custom AI-powered RAG system with Redis semantic caching for fast, accurate data retrieval. Includes API integration, AI pipeline setup, and optional dashboard for managing queries and datasets efficiently.