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I will build custom ai agent and local rag pipeline in python
Sayyam Shahbaz
About this gig
Are you looking to build a secure, local AI agent or RAG pipeline without expensive cloud API costs? As an IBM & Microsoft Certified AI Engineer, I specialize in building offline-first Python AI systems tailored to your business data.
I architect production-grade local LLM workspaces that transform proprietary documents into searchable intelligence, ensuring your data remains 100% private.
What I Can Build For You:
- Custom AI Agent Workflows: Dual-model orchestration (DeepSeek-R1, Qwen) utilizing self-correction and validation loops.
- Intelligent RAG Pipelines: High-performance retrieval-augmented generation via ChromaDB for automated text/PDF ingestion.
- Local LLM Integration: Smooth hosting configurations utilizing Ollama, LM Studio, or Llama models to run completely locally.
- Interactive Python AI UIs: Sleek, user-friendly dashboards built with Streamlit for live data streaming and chat.
- Enterprise Architecture: Schema validation powered by Pydantic and secure persistent memory built on SQLite.
Your data stays entirely under your control. Let's build a powerful AI tool optimized for your workflow.
Message me to start!
Get to know Sayyam Shahbaz
Sayyam Shahbaz
AI Engineer, Python Automation, Computer Vision
- FromPakistan
- Member sinceApr 2023
- Last delivery1 year
Languages
English
I'm Sayyam Shahbaz, a certified AI & Software Engineer (IBM, Microsoft, Imperial College London). I bridge the gap between machine learning and business operations, building automated workflows and AI-powered apps.
My Stack:
AI: RAG, Local LLMs (Ollama/DeepSeek), Vector DBs
Automation: Python, Meta/Google APIs
Vision: OpenCV, YOLO, MediaPipe
Mobile ML: Android (Kotlin), TF Lite, PyTorch
Whether you need a secure AI agent, computer vision tracker, or on-device ML model, let's turn your idea into reality!
My Portfolio
FAQ
What is a local RAG pipeline and why do I need it?
A RAG pipeline allows a custom AI agent to read and understand your specific business documents (like PDFs or Markdown). By using a local LLM, you pay absolutely zero monthly cloud API fees, and your sensitive data remains 100% private and secure on your own machine.
Which models and tools do you use for the AI agent?
I specialize in Python AI development. I build vector databases using ChromaDB and orchestrate powerful local models like DeepSeek-R1, Qwen, and Llama through Ollama. For the frontend, I create sleek interactive dashboards using Streamlit AI.
Can you ensure the AI won't hallucinate or make up facts?
Yes! I architect enterprise-grade AI agents using self-correction loops and schema validation. Because the RAG pipeline forces the model to cite your uploaded documents, the answers are grounded, highly accurate, and reliable for business use.
Do I need an expensive computer to run a local LLM?
Running a local LLM via Ollama does require some baseline RAM and GPU resources. However, I optimize the models for your specific hardware. If needed, we can also build a hybrid setup that ensures your system runs smoothly without lagging.
