You will get AI chatbot, AI agent, RAG, n8n, Zapier or Make automation
Top Rated
Project details
I will help businesses implement AI chatbots, AI agents, RAG systems, and workflow automation using n8n, Make.com, Python, FastAPI, OpenAI API, Claude API, and LangChain. My services include building custom AI chatbots for customer support, lead generation, onboarding, and internal helpdesks, developing autonomous AI agents capable of reasoning and executing multi-step workflows, and integrating RAG knowledge bases for semantic search and intelligent Q&A. I also automate business workflows, connecting CRMs, ERPs, databases, and third-party platforms through APIs and webhooks to streamline operations. Every project is production-ready, fully integrated, and optimized for scalability, providing measurable impact. Clients will receive a clear implementation plan, end-to-end AI solutions, and guidance on AI workflow deployment. Ideal for businesses in Healthcare, Fintech, E-commerce, SaaS, Logistics, Marketing, Education, and Enterprise operations seeking to leverage AI for automation, efficiency, and intelligent decision-making.
Machine Learning Tools
Amazon SageMaker, Azure Machine Learning, ChatGPT, deeplearn.js, GitHub Copilot, Google Sheets, GPT-3, NumPy, pandas, Python, PyTorch, SQL, Tableau, TensorFlowWhat's included
| Service Tiers |
Starter
$150
|
Standard
$400
|
Advanced
$600
|
|---|---|---|---|
| Delivery Time | 2 days | 5 days | 7 days |
Number of Revisions | Unlimited | Unlimited | Unlimited |
Number of Model Variations | 1 | 3 | 5 |
Number of Scenarios | 1 | 3 | 5 |
Number of Graphs/Charts | 1 | 3 | 5 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code | - | - |
Frequently asked questions
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MT
Muneeb T.
Jan 9, 2026
Computer Vision / Deep Learning Engineer – Sports Video Analysis
Found issue and provided great results on our object detection project, implementing a YOLO-based model that exceeded our accuracy requirements. Her technical skills in computer vision are solid, and she communicated progress clearly throughout. I highly recommend her and would definitely work with her again on future CV projects
IM
Ibrahim M.
Jan 7, 2026
Full Stack Developer Needed - React.js & Django Healthcare Platform
Great experience working with her. She communicated clearly, met deadlines, and delivered high quality work. I’d be happy to work with her again and recommend her.
About Habib
AI Automation | n8n, Make, Zapier, LangGraph | RAG | AI Agents| Python
100%
Job Success
Bolingbrook, United States - 2:58 am local time
𝙏𝙝𝙖𝙩’𝙨 𝙩𝙝𝙚 𝙟𝙤𝙗:
I build AI systems that give you your hours back.
𝙈𝙮 𝙩𝙤𝙤𝙡𝙨 𝙖𝙧𝙚 n8n, Make, Zapier, Python, LangGraph, OpenAI, Claude, Pinecone, and API integrations. My rule is simple: everything I build has to survive production, because that is where most AI automation quietly dies.
What that looks like in practice:
𝙄𝙣𝙫𝙤𝙞𝙘𝙚 𝙥𝙧𝙤𝙘𝙚𝙨𝙨𝙞𝙣𝙜, accounting workflow. Email arrives in Outlook, Claude extracts the data, entry lands in QuickBooks, and the document files itself in Dropbox. 85% of invoices never touch a human. The other 15% get flagged for review on purpose, because an automation that never asks for help is one that hides its mistakes.
𝙋𝙧𝙤𝙥𝙤𝙨𝙖𝙡 𝙜𝙚𝙣𝙚𝙧𝙖𝙩𝙞𝙤𝙣, retreat planning business. RAG over their full knowledge base with Pinecone, Claude drafts the proposal, and 14 Google Docs templates assemble the final output. 3 hours of work became 2 minutes. The owner got her evenings back.
𝘾𝙤𝙢𝙥𝙡𝙚𝙭 𝙪𝙩𝙞𝙡𝙞𝙩𝙮 𝙗𝙞𝙡𝙡 𝙥𝙧𝙤𝙘𝙚𝙨𝙨𝙞𝙣𝙜 𝙖𝙩 𝙨𝙘𝙖𝙡𝙚. Built a 10-agent LangGraph pipeline on Azure for high-volume document processing. A cheaper model handles the routine 90%, a stronger model handles edge cases, validation agents check totals and missing fields, and dead-letter queues keep one bad bill from killing the whole run. The result: stable processing, controlled AI costs, and a system that scales without needing a person to watch every batch.
𝘼𝙄 𝙘𝙖𝙡𝙡𝙞𝙣𝙜 𝙖𝙜𝙚𝙣𝙩, healthcare screening workflow. Built an AI phone agent that calls patients, asks intake questions, collects structured answers, handles follow-up logic, and routes edge cases to a human. The goal was not just “voice AI,” but a reliable workflow: clean call flow, safe handoff, transcript capture, CRM/update logic, and human review when needed.
𝙍𝙚𝙨𝙘𝙪𝙚 𝙟𝙤𝙗. A marketing agency’s Zapier pipeline kept timing out on long AI generation steps. I rebuilt it on Make and n8n: posts, image prompts, brand-consistent images, and automated publishing. Their team stopped babysitting it the same week.
And when an official integration breaks, I fix it at the API level. n8n’s Xero node died for newer apps this year. I shipped the OAuth2 workaround while everyone else was waiting for a patch.
Before I automate anything, I map your actual process. Automating a broken process just makes mistakes faster, and I’d rather tell you that on day one than bill you for it.
Best fit: 𝙖𝙘𝙘𝙤𝙪𝙣𝙩𝙞𝙣𝙜 𝙖𝙣𝙙 𝙥𝙧𝙤𝙛𝙚𝙨𝙨𝙞𝙤𝙣𝙖𝙡 𝙨𝙚𝙧𝙫𝙞𝙘𝙚𝙨 𝙬𝙤𝙧𝙠𝙛𝙡𝙤𝙬𝙨, 𝙖𝙜𝙚𝙣𝙘𝙮 𝙤𝙥𝙚𝙧𝙖𝙩𝙞𝙤𝙣𝙨, 𝙖𝙞 𝙘𝙖𝙡𝙡𝙞𝙣𝙜 𝙖𝙜𝙚𝙣𝙩𝙨, 𝙖𝙣𝙙 𝙙𝙖𝙩𝙖-𝙝𝙚𝙖𝙫𝙮 𝙗𝙖𝙘𝙠 𝙤𝙛𝙛𝙞𝙘𝙚 𝙥𝙧𝙤𝙘𝙚𝙨𝙨𝙚𝙨.
Tell me which task is eating your team alive and what tools you run. I’ll give you a straight answer on whether it’s worth automating, what it costs, and what it saves.
Keywords:
AI Automation · LangChain · n8n · Make .com · Zapier · OpenAI API · Claude API · Chatbot Development · RAG Systems · LlamaIndex · Pinecone · FastAPI · Python · API Integration · AI Agent Development · LLM Integration · Workflow Automation · Vector Databases · GPT-4 · Business Process Automation
Steps for completing your project
After purchasing the project, send requirements so Habib can start the project.
Delivery time starts when Habib receives requirements from you.
Habib works on your project following the steps below.
Revisions may occur after the delivery date.
Client Requirements Submission
Client provides project details, business goals, workflow requirements, preferred AI tools, datasets, and integration platforms.
Workflow & Architecture Planning
Analyze client workflow, design AI architecture, select automation platforms, plan chatbots, agents, RAG systems, and API connections.