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English
$
USD
I will build a custom ai chatbot using nlp and rag for your business
Faiza Soomro
About this gig
Your customers ask the same questions over and over or worse, they need answers from your documents and your current bot just can't find them.
I build custom AI chatbots that actually understand your content. Choose a lightweight NLP-based FAQ bot for a well-defined set of repeat questions, or a full RAG (Retrieval-Augmented Generation) chatbot that searches your own documents and generates accurate, grounded answers in multiple languages not generic guesses.
What you get:
A working chatbot deployed as a live web app
Trained on your FAQs or your own documents
Clean, simple interface your customers can use immediately
Full source code on every package no lock-in, no black box
I've built and deployed multiple chatbots FAQ-matching bots using NLP, and full multilingual RAG systems using vector search and LLM integration via LangChain and Gemini. I focus on chatbots that give correct, sourced answers, not just chatbots that sound smart.
Message me before ordering if your project needs something outside these packages happy to scope it first.
Get to know Faiza Soomro
Faiza Soomro
Full Stack Developer and AI ML Engineer, Python, Django, React, Chatbots, NLP
- FromPakistan
- Member sinceApr 2024
- Avg. response time1 hour
Languages
English
Hi, I'm Faiza — an AI/ML Engineer and Full Stack Developer from Pakistan. I build chatbots, computer vision systems, and full-stack web apps that actually work in production, not just demos.
Recent builds: a RAG chatbot using vector search and Gemini, a real-time object detection system with YOLOv8, and an ML credit-scoring model for loan underwriting.
Core stack: Python, Django, Flask, FastAPI, React, MySQL, PyTorch, OpenCV.
I care about clean code and clear communication. Let's talk about what you're building.
My Portfolio
FAQ
What's the difference between the FAQ bot and the RAG chatbot?
The FAQ bot matches questions against a fixed list you provide — fast and cheap for repeat questions. The RAG chatbot searches your actual documents and generates answers from retrieved content — better for open-ended queries.
Do I need to already have my FAQ content or documents ready?
It helps, but it's not required. If your content isn't organized yet, message me first and I can help structure it as part of the project.
Which languages does the chatbot support?
The RAG-based packages (Standard and Premium) support multiple languages out of the box. The Basic FAQ bot is scoped for a single language — message me if you need multi-language on Basic, it's available as an add-on.
Can this integrate with my CRM or database?
This isn't included by default, but it's available as an add-on. Since every CRM's API is different, please message me with which system you use before ordering so I can confirm feasibility and timeline.
What happens if the chatbot doesn't know an answer?
It's built to say so honestly instead of guessing. I set a confidence threshold so the bot only answers when it's actually confident in the match — this avoids the common problem of chatbots confidently giving wrong answers.
Do you offer support after delivery?
Yes. Each package includes a set number of revisions, and you can add extra revision rounds if needed. For ongoing changes beyond that, message me to discuss an arrangement.
