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I will build python rag agents using microsoft foundry
Aryan
Over deze dienst
Do you need an advanced AI agent that accurately queries complex corporate data without hallucinating or risking privacy?
I build custom, enterprise-grade AI applications and Retrieval-Augmented Generation (RAG) pipelines using Python and Microsoft Foundry (formerly Azure AI Studio). I bridge the gap between code-first AI logic and secure enterprise deployment.
What I offer:
- Custom Python RAG pipelines using LangChain & LlamaIndex
- Semantic document search with Qdrant, Chroma, or Azure AI Search
- Advanced text chunking, metadata filtering, and parent-child retrieval
- Secure hosting and multi-agent workflows inside Microsoft Foundry Portal
- FastAPI or Flask backends to connect custom AI to external systems
- Secure data grounding via Foundry IQ (SharePoint, Fabric, Blob storage)
Whether you need to analyze complex multi-page financial reports, legal contracts, or technical compliance documents, I build scalable, secure AI systems tailored to your architecture.
Please send a message with your data structure and project requirements before placing an order so we can design the ideal AI blueprint!
Maak kennis met Aryan
Aryan
Enterprise AI Engineer, Microsoft Foundry, Copilot Studio, Python RAG
- Afkomstig uitIndia
- Lid sindsnov 2023
- Gem. reactietijd1 uur
- Laatste levering7 maanden
Talen
Engels, Hindi, Duits, Spaans
Enterprise AI Engineer specializing in custom automation and intelligent agents. I build secure, data-driven AI systems using Microsoft Foundry, Copilot Studio, Power Automate, and custom Python RAG pipelines. Whether you need an autonomous agent grounded securely in your internal company documents (SharePoint/Databases) or advanced multi-step workflow automations that sync seamlessly with Microsoft Teams and your enterprise APIs, I deliver production-ready, secure solutions that eliminate manual overhead. Let’s build your AI ecosystem safely.
Mijn portfolio
Veelgestelde vragen
Is my data safe? Will my company documents be used to train public AI models?
No, your data is completely secure. By architecting your custom Python RAG pipeline within Microsoft Foundry and your private Microsoft 365 tenant, your data remains strictly isolated. No public models are trained on your proprietary business information, ensuring full data privacy compliance.
Why choose a custom Python RAG pipeline over out-of-the-box AI tools?
Standard out-of-the-box chatbots frequently hallucinate and struggle with complex file layouts, unstructured text, or large databases. A custom Python backend built with LangChain or LlamaIndex allows for advanced chunking strategies, metadata filtering, and semantic matching, ensuring highly accura
What vector databases do you support for semantic data storage?
I work natively with high-performance vector databases optimized for enterprise data, including Qdrant, Chroma, and Azure AI Search. I configure appropriate indexing, collection schemas, and metadata structures to match the scale and speed requirements of your business data.
What do I need to provide to get started with the project?
To begin, you will need to provide an overview of your current data architecture (e.g., SharePoint folders, local databases, or Blob storage) and a sample set of the files you want the AI agent to interact with. If we are deploying to Microsoft Foundry, temporary environment or tenant access will be
Can this custom Python AI agent be integrated back into my Microsoft Teams or Copilot?
Absolutely. My core specialty is bridging code-first AI with enterprise workflows. I deploy the custom Python RAG pipeline as a secure API (using FastAPI), which can then be easily connected directly into Microsoft Copilot Studio or triggered automatically via Power Automate cloud flows.
