Muhammad F.

I build AI agents and n8n automations that handle real business data reliably: pulling it from your tools, processing it with OpenAI or Claude, and pushing clean results back into your CRM, database, or team channels. With 7+ years in Python, API integration, and data engineering, I build the parts most automations skip: validation, retries, error handling, logging, and human approval where it matters. That is the difference between a workflow that works in a demo and one your team can rely on every day. Clients usually come to me when: "We want to use AI, but we don't know how to connect it to our systems." "Our n8n workflow works sometimes but keeps breaking." "Our team spends hours moving, cleaning, and checking data by hand." "We need an AI agent that takes actions, not just answers questions." What I build: AI agents that take actions across your tools, databases, and APIs n8n workflows for multi-step automation, database upserts, and scheduled syncs AI data pipelines that extract, clean, enrich, and load data using LLMs RAG assistants trained on your documents and knowledge base AI document processing for PDFs, invoices, forms, and emails OpenAI, Claude, and Gemini integrations with your existing systems Fixes for unreliable n8n or Make workflows that fail under real volume Custom Python automation when no-code tools reach their limits Recent work: Built an LLM-integrated data pipeline using Python, Airflow, dbt, PostgreSQL, and LLM APIs Built n8n pipelines for data upserts and an Airtable to PostgreSQL integration Built a Python and SQL ETL process to load and update a 10GB database Delivered a HIPAA-compliant healthcare data pipeline on Azure Stack: n8n | Make | Zapier | OpenAI API | Claude | LangChain | RAG | Python | API Integration | PostgreSQL | Airtable | BigQuery | Snowflake | Airflow Send me the process you want to automate. I'll tell you what can be automated, which tools fit, and where AI adds real value versus where simple logic works better.