Aatizaz Khan
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Service

RAG Pipelines & Systems

I build RAG (retrieval-augmented generation) pipelines that let an AI model answer questions from your own documents and data. Your content is embedded into a vector database, the most relevant passages are retrieved for each question, and the model answers from them, with sources.

What you get

  • Document ingestion and chunking pipelines
  • Embeddings and vector search
  • Question-answering assistants with source citations
  • An API or chat interface for your team or customers

Tech stack

  • Python
  • LangChain
  • Vector databases
  • Hugging Face
  • LLM APIs (Claude, OpenAI)
  • FastAPI

How it works

  1. 01

    Scope

    You share the idea and requirements; I reply within two days with questions, then a fixed-price quote that itemises each deliverable.

  2. 02

    Build

    Work happens in stages with regular progress updates. Changes mid-build are assessed and planned in, not refused.

  3. 03

    Review

    Two rounds of revisions are included. Anything beyond that, or a change in scope, is quoted separately.

  4. 04

    Launch & support

    Release, handover, and two weeks of support included. Ongoing care is available as a monthly retainer.

Timeline & pricing

Scoped per project; you get a fixed timeline with the quote. Every project has a fixed price, quoted after I review your requirements, with each deliverable itemised.

Questions

Use RAG when the AI must answer from specific, changing information such as documents, policies or product data. Use fine-tuning when you need the model to learn a new task, style or format. Many products need RAG only, because it updates as soon as your documents do.

Most text sources work: PDFs, web pages, help-centre articles, internal docs and database records. Each source is split into passages, embedded and stored in a vector database, so the assistant can retrieve and quote the right passage when answering a question.

Other services

Available for work

Got an idea worth building?

Start a project

Start a project