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I will build an enterprise rag system with vector database and llm
Sabhi Ahmad
About this gig
Is your valuable business knowledge scattered across PDFs, documents, and internal data? I build customized RAG systems that connect your knowledge to LLMs, turning it into an intelligent and searchable AI application.
I'm Sabhi, an AI/ML and Software Engineering specialist with a Masters degree in Artificial Intelligence and 7+ years of industry experience. I build practical AI systems with a focus on reliable development, maintainable architecture, and specific business needs.
What I Build
- RAG & AI knowledge bases
- Document and PDF chatbots
- Knowledge assistants & enterprise chatbots
- Semantic and hybrid search
- Vector database-powered applications
- LLM-powered knowledge systems
How It Works
- Your Data
- Processing & Embeddings
- Retrieval
- Relevant Context
- LLM
- Grounded Response
Depending on your package, I can implement metadata filtering, source citations, semantic or hybrid search, reranking, API integrations, RAG evaluation, and cloud deployment.
I engineer systems around your specific use case rather than offering a one-size-fits-all PDF chatbot.
Have a specific AI solution in mind? Message me before ordering if you need a custom RAG architecture
Get to know Sabhi Ahmad
Sabhi Ahmad
Building AI agents, RAG, SaaS and computer vision systems
- FromPakistan
- Member sinceMar 2025
- Avg. response time1 hour
Languages
English, German, Arabic
Hello! I'm Sabhi, AI/ML and Software Engineering specialist with a Master's degree in Artificial Intelligence and +7 years if industry experience. I specialize in:
1) AI Agents & Multi-Agent Systems
2) RAG, Vector Databases & AI Chatbots
3) AI SaaS, LLM Apps & Custom AI Software
4) Computer Vision, Object Detection & Video Analytics
I combine AI/ML expertise with software engineering to build scalable, production-focused solutions for business needs, from intelligent automation to AI products. I focus on architecture, reliable development, and long term value, Let's build your AI solution!
My Portfolio
Other AI Development Services I Offer
FAQ
Which RAG package is right for my project?
Basic is suited to a focused RAG prototype. Standard is for a custom knowledge system with semantic search, metadata filtering, citations, and one API integration. Premium adds hybrid search, reranking, evaluation, integrations, and cloud deployment for advanced requirements.
What is RAG, and why would my business need it?
RAG (Retrieval-Augmented Generation) allows an LLM to retrieve relevant information from your own documents or data before generating an answer. This connects the model to your business knowledge and can provide more relevant, context-based responses than relying only on general model knowledge.
Can my PDFs, documents, or business data be used in a RAG system?
Yes. Depending on the project, I can process PDFs, text documents, and other suitable structured or unstructured data. The supported scope depends on data format, volume, complexity, and your selected package. Large or complex datasets can be scoped separately
Can you build a document chatbot, AI knowledge base, or knowledge assistant?
Yes. I can build document/PDF chatbots, AI knowledge bases, and LLM-powered knowledge assistants that retrieve relevant information from your supplied data. The functionality and complexity depend on the selected package and can range from focused document Q&A to advanced knowledge applications.
Can you integrate my preferred vector database with a RAG system?
Yes. I can implement a suitable vector database such as Chroma, pgvector, Qdrant, Pinecone, or Weaviate based on your requirements. Each package includes one vector database implementation; the final choice depends on the application's data, retrieval, and deployment needs.
Can you implement semantic search, hybrid search, and reranking?
Yes. Basic and Standard packages support vector/semantic retrieval, with Standard adding metadata filtering. Premium can implement semantic and keyword retrieval, hybrid search, and reranking for more advanced retrieval requirements and improved relevance within the agreed scope.
Can you integrate my preferred LLM with the RAG application?
Yes. I can integrate a suitable LLM through its supported API and connect it with the retrieval pipeline. Each package includes one primary LLM integration. The specific model should be selected according to your application's requirements, capabilities, and available API access.
Can you connect the RAG system to APIs or external business data?
Yes. Standard includes one standard API/data integration, while Premium includes up to two. Examples include REST APIs or external data sources. Complex CRM workflows, synchronization, custom middleware, or extensive integrations require separate scope and may be handled through a custom offer.
Can you provide citations and grounded answers?
Yes. Depending on the selected package, the RAG application can provide source references or citations showing where retrieved information comes from. RAG can help ground LLM responses in your supplied knowledge, but no AI system can guarantee perfect accuracy
Can you deploy a RAG application to the cloud?
Yes. Premium includes one cloud deployment of the delivered application/backend. Basic is focused on local/prototype setup, while Standard focuses on application/backend setup. Cloud infrastructure, account costs, and requirements beyond the package scope are handled separately.
