You will get Custom RAG application using OpenAI and Langchain
Rising Talent
Rising Talent
Project details
Your documents already have the answers — I build the AI
that delivers them instantly, grounded strictly in your
content with zero hallucinations.
Upload PDFs, Word docs, or your knowledge base and get a
RAG chatbot that retrieves accurately, reranks for
precision, and cites every source. Deployable as a web
widget, internal tool, or API endpoint.
Deployment — your choice:
— Self-hosted (open-source models + local vector DB)
for full data privacy and zero per-query cost
— Claude or OpenAI for fastest quality output
— AWS Bedrock for enterprise-grade infrastructure
I build accuracy evaluation in from day one — so you
measure answer quality, not guess at it.
Works with: PDF, Word, web pages, and most text formats.
New documents can be added anytime — pipeline supports
ongoing ingestion.
that delivers them instantly, grounded strictly in your
content with zero hallucinations.
Upload PDFs, Word docs, or your knowledge base and get a
RAG chatbot that retrieves accurately, reranks for
precision, and cites every source. Deployable as a web
widget, internal tool, or API endpoint.
Deployment — your choice:
— Self-hosted (open-source models + local vector DB)
for full data privacy and zero per-query cost
— Claude or OpenAI for fastest quality output
— AWS Bedrock for enterprise-grade infrastructure
I build accuracy evaluation in from day one — so you
measure answer quality, not guess at it.
Works with: PDF, Word, web pages, and most text formats.
New documents can be added anytime — pipeline supports
ongoing ingestion.
Programming Languages
PHP, PythonWhat's included
| Service Tiers |
Starter
$500
|
Standard
$1,000
|
Advanced
$2,000
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 18 days |
Number of Revisions | 1 | 2 | 2 |
Design Customization | - | - | - |
Content Upload | - | - | - |
Responsive Design | - | - | - |
Source Code | - | - | - |
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Robert S.
Jun 15, 2026
Someone to Create AI Websites for Our 100,000+ Clients -
Excellent designer! Professional, creative, responsive, and easy to work with. Delivered a beautiful, high-quality website on time and exceeded expectations. Highly recommend and would gladly work together again.
About Junaid Ali
FullStack AI Developer, AI Agents, RAG, Chatbots, Computer Vision
Lahore, Pakistan - 1:51 pm local time
My strength is blending AI with full-stack development to create complete, production-ready solutions so you get a working product around the AI, not just a script you have to wire up yourself.
I cover ground most AI devs skip: computer vision (YOLO, OpenCV, GANs) and geospatial/remote-sensing AI (Google Earth Engine), useful when your problem isn't only text.
Most of what I do falls into four buckets:
- AI agents & agentic workflows: LangGraph, multi-agent orchestration, tool-using systems that handle real tasks.|
- RAG & chatbots: accurate, source-grounded answers over your own data (LangChain, LlamaIndex, Pinecone/Qdrant, OpenAI & Claude).
- Workflow automation & AI integration: n8n, Makecom, Zapier, GoHighLevel, WhatsApp API; connecting AI to the tools you already use.
- Computer vision: object detection, segmentation, and image analysis with YOLO, OpenCV, and PyTorch from medical imaging to satellite and drone imagery (Google Earth Engine)
The way I work: you tell me what you're trying to do, I give you a straight take on the best approach before you commit, then I build it and keep you in the loop. Fast replies, no jargon, no disappearing.
Take a look at my portfolio below for real examples, and send a message if you'd like to talk through your project.
𝑱𝒖𝒏𝒂𝒊𝒅 𝑨𝒍𝒊
Steps for completing your project
After purchasing the project, send requirements so Junaid Ali can start the project.
Delivery time starts when Junaid Ali receives requirements from you.
Junaid Ali works on your project following the steps below.
Revisions may occur after the delivery date.
Step 1: Discovery
I review your documents and use case, then design the retrieval pipeline before writing a single line of code.
Step 2: Build & Test
RAG pipeline built, hybrid retrieval and reranking tested for accuracy, revision completed on your feedback.