I will build custom ai with vector embeddings, gpt models, and vector database


About this gig
Standard AI models don't know your business data.
To fix this, you don't need a smarter modelyou need Vector Embeddings.
Hi, I am Ali! I build Custom AI solutions that actually understand your documents. I bridge the gap between LLMs (like GPT-4) and your data using robust Vector Databases.
The Strategy (RAG):
I use RAG (Retrieval-Augmented Generation). By converting your text/PDFs into Vector Embeddings, I give your AI "long-term memory." It allows the AI to search your files and provide accurate answers using Semantic Search.
What I Offer:
Vector DB Setup: Expert configuration of Pinecone, ChromaDB, Weaviate, or Milvus.
Data Ingestion: Processing your PDFs/CSVs into clean embeddings.
LangChain Integration: Connecting your database to GPT-4 or Gemini for intelligent chat.
Tech Stack:
- Code: Python, TypeScript.
- DBs: Pinecone, ChromaDB, Supabase.
- AI: OpenAI, Llama 3, HuggingFace.
Ready to give your AI a brain?
Please message me before ordering so we can discuss your data needs!
Get to know Ali Haider
Chatbot Developer
- FromPakistan
- Member sinceSep 2025
- Avg. response time1 hour
Languages
English, Urdu, Punjabi
My Portfolio
FAQ
What is a Vector Embedding?
It is a way to translate text into numbers so an AI can understand the "meaning" and context behind your data, allowing for smart searching and retrieval.
Which Vector Databases do you support?
I work with all major providers including Pinecone, ChromaDB, Weaviate, Milvus, and pgvector.
Can you build a Chatbot that reads my PDF files?
Yes! This is called RAG (Retrieval-Augmented Generation). I use vector embeddings to let the AI "read" your PDF and answer questions accurately.

