I will build an ai semantic search engine by vector search, embeddings, and clip model


About this gig
Do you want a search system that understands meaning, not just keywords?
I build advanced AI semantic search engines using vector embeddings, CLIP models, and LLM-powered retrieval systems perfect for documents, images, e-commerce, knowledge bases, or custom databases.
Unlike normal search, semantic search finds results based on context, similarity, and intent.
No more exact matches users get truly intelligent, relevant responses.
If you're looking to bring Google-level search intelligence to your application, you're in the right place.
What I Can Build for You
Semantic document search
Image search (CLIP-based similarity search)
Product search for e-commerce
Knowledge-base / FAQ semantic search
Multi-modal search (text image, image text)
Embeddings-based search (OpenAI, SentenceTransformers)
Vector database setup (Pinecone, Chroma, Weaviate, Milvus)
RAG-based search systems
Next.js + Python-backed search interfaces
API endpoints for integration into any web app
Respect third-party rights
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Get to know Wasam Khan
Full Stack Engineer
- FromPakistan
- Member sinceSep 2021
Languages
English
My Portfolio
FAQ
What is semantic search?
Semantic search finds results based on meaning, not keywords. It's far more intelligent than traditional search.
Can you add this search engine to my existing website?
Yes — I can integrate the search API or UI into any website or dashboard.
Do you support both images and documents?
Yes — I can build: • Image search (CLIP) • Document search • Multi-modal search (image ↔ text)
What vector database is best?
For production: Pinecone / Weaviate For budget-friendly: ChromaDB
Will you deploy the system for me?
Yes — I can deploy on Vercel, AWS, Render, Railway, or your server.
