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$
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I will build custom generative ai models, rag, and nlp solutions
About this Gig
Stop relying on generic AI. Start building Private Intelligence.
Welcome to the Generative AI Division of Khan's AI. We are a registered Research & Development (R&D) firm specializing in Natural Language Processing (NLP) and Large Language Models (LLM).
While most developers simply connect your data to public APIs (risking your privacy), we engineer custom, secure data pipelines. We focus on Retrieval-Augmented Generation (RAG) and Model Fine-Tuning, allowing your business to leverage AI without leaking sensitive data to the public cloud.
Our Scientific Approach:
- Custom RAG Architectures: We build vector databases (Pinecone/Chroma) that allow LLMs to "read" and cite your internal PDFs, SQL databases, and legal documents with zero hallucinations.
- Model Fine-Tuning: We adapt open-source models (Llama 3, Mistral, Falcon) to understand your specific industry jargon (Medical, Legal, Engineering).
- Agentic Workflows: Autonomous AI agents that can browse the web, scrape data, and execute tasksnot just chat.
️ Our Tech Stack:
- Frameworks: PyTorch, LangChain, LlamaIndex, Haystack.
- Models: GPT-4o, Claude 3.5, Llama 3, Mistral 7B (Quantized).
- Vector DBs: Pinecone, Weaviate, Milvus, ChromaDB.
Other Data Science & ML Services I Offer
FAQ
Will my company data be shared with OpenAI/Public models?
For our "Standard" and "Premium" packages, we prioritize privacy. We can build Local RAG systems using open-source models (like Llama 3) that run entirely on your private cloud or local server. Your data never leaves your infrastructure.
Can you sign a Non-Disclosure Agreement (NDA)?
Yes. As Khan's AI is a registered R&D firm, we are happy to sign an NDA to protect your proprietary datasets and intellectual property before we begin work.
Do I need expensive GPU servers to run these models?
Not necessarily. We specialize in Quantization (4-bit/8-bit), which allows powerful LLMs to run on cheaper consumer hardware or affordable cloud instances (like AWS t3 or Google Colab T4), saving you thousands in hosting costs.
What is the difference between RAG and Fine-Tuning?
RAG (Standard Package) is like giving the AI a textbook to read—it answers based on your documents. Fine-Tuning (Premium Package) is like sending the AI to medical school, it learns a new skill or writing style permanently. We will advise you on which is best for your goal.
