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Fiverr Pro
English
$
USD
I will develop custom rag, ai agents and python automation for your business
Hammad Ishaq
About this gig
Stop paying for AI demos that break in production.
I am a Python AI developer who builds RAG systems, AI agents, and automation
that actually run 24/7 not toy chatbots that hallucinate on real data.
WHAT I DELIVER:
- RAG Chatbots Talk to your PDFs, Notion, websites with hallucination-free answers using LangChain + Pinecone/pgvector
- AI Agents Tool-calling agents that browse, search, scrape, and execute real tasks
- Python Automation FastAPI backends, web scraping, workflow automation with n8n
- LLM Integration GPT, Claude, Gemini, Llama integrated into your existing app
- Vector Databases Production-grade retrieval pipelines that scale
WHY ME:
- Production-first: I write code that handles edge cases, not Streamlit demos
- Your API keys, your source code, your data zero vendor lock-in
- Clear communication and async updates throughout
- Free 7-day bug-fix warranty on every project
TECH STACK:
Python, LangChain, FastAPI, OpenAI, Anthropic Claude, Pinecone, pgvector, AWS, n8n
Best for SaaS founders, e-commerce, agencies, and SMBs who need real AI that ships.
Message me before ordering so I can map the right architecture to your use case.
Get to know Hammad Ishaq
Hammad Ishaq
AIML Engineer
- FromPakistan
- Member sinceMay 2026
- Avg. response time1 hour
Languages
Urdu, English, Punjabi, Arabic
My journey began in 2021 as a Node.js developer, but curiosity pulled me deep into machine learning, where I've spent years mastering deep learning, computer vision, predictive modeling, and model deployment at scale. Certified by Stanford, DeepLearning.AI, and IBM, I design and deploy production-grade ML systems, architect agentic AI pipelines and multi-agent workflows with LangChain and LangGraph, fine-tune LLMs, and build RAG architectures for context-aware AI. Skilled in end-to-end MLOps using Docker, FastAPI, and cloud platforms engineering intelligent systems that deliver real impact.
FAQ
What is RAG and why do I need it?
RAG (Retrieval Augmented Generation) makes the AI answer only from your data — your PDFs, website, or database — instead of guessing. This eliminates hallucinations and keeps responses accurate. If your chatbot must answer factually about your business, you need RAG.
Which LLMs and tools do you work with?
GPT-5, GPT-4o, Claude (Anthropic), Gemini, Llama, and Mistral. For vector databases: Pinecone, pgvector, Qdrant, Chroma. Frameworks: LangChain, LlamaIndex, FastAPI. I pick the right stack based on your budget and privacy needs.
Do I own the source code and data?
Yes, 100%. You get full source code, all API keys stay in your account, and your data lives in your infrastructure. No vendor lock-in. I can deploy on your AWS, GCP, or hand off for your team to deploy.
Do I need to provide API keys?
Yes. You provide your own OpenAI, Anthropic, or other LLM API keys so you control usage and billing. I'll guide you through setup if you're new to it.
Can the AI agent connect to my existing tools?
Yes. I integrate with HubSpot, Salesforce, Slack, Notion, Google Drive, WhatsApp, Zapier, n8n, and any tool with an API. Agents can read data, create records, and trigger workflows automatically.
What do you need from me to start?
A clear description of the problem, sample data (PDFs, sheets, URLs), and access to any APIs or accounts the agent must connect to. A short call or message thread helps me scope correctly.
