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I will build custom llm apps and generative ai software
Muhammad Shazad
About this gig
I will build, deploy, and scale custom LLM applications and text-based AI software for your business or startup.
While many developers simply connect pre-built automation tools, I provide full-stack AI software engineering. I specialize in Natural Language Processing (NLP), Large Language Models, and deep learning frameworks to build standalone AI products designed for performance, accuracy, and scale.
What I can build for you:
- Custom LLM Applications: Full-stack web apps powered by OpenAI, Anthropic, or open-source local models.
- Advanced RAG Systems: Enterprise-grade document retrieval using Vector Databases (Chroma, Pinecone) for accurate "chat-with-your-data" solutions.
- Autonomous AI Agents: LangChain and LangGraph architectures for research, data extraction, and complex reasoning tasks.
- High-Performance APIs: Robust REST APIs built with FastAPI to integrate text-based AI directly into your current software.
My Tech Stack:
- AI/NLP: LangChain, LangGraph, HuggingFace, OpenAI API
- Backend & DB: Python, FastAPI, Vector Databases
- Deployment: Docker, Cloud Infrastructure (Azure/GCP), API Monitoring
Let's discuss your system architecture. Please message me before placing an order!
Get to know Muhammad Shazad
Muhammad Shazad
GenAI and Computer Vision Engineer
- FromFinland
- Member sinceJul 2020
- Avg. response time1 hour
- Last delivery7 months
Languages
English, Urdu, Chinese
I build production-ready LLM solutions, multi-agent frameworks (LangGraph/CrewAI), and advanced RAG systems. I specialize in fine-tuning models (LoRA/QLora), implementing safety guardrails, and deploying scalable cloud-native apps on AWS/Azure.
Beyond GenAI, I offer high-end Computer Vision services: object detection, tracking, and segmentation. I automate complex workflows using n8n and Model Context Protocol (MCP) to bridge LLMs with external tools. From Document Intelligence to SDLC automation, I deliver secure, enterprise-grade AI. Let's build.
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FAQ
Will my company's private data be used to train public AI models?
No. I design systems using Retrieval-Augmented Generation (RAG) and strict API protocols to ensure your proprietary data is only used as temporary context for your specific queries, never for training public models.
Can you build this using open-source models so I don't have to pay OpenAI API fees?
Yes! Depending on your hardware and cloud infrastructure, I can build your application using powerful open-source models like Llama or DeepSeek, which gives you complete control over your data and eliminates recurring API token costs.
How do you prevent the AI from "hallucinating" or making up facts?
I build strict routing logic and deterministic lookups into the system. By grounding the LLM in your specific documents (using advanced chunking and metadata filtering), the AI is forced to cite its sources and will refuse to answer if the information isn't in your database.
