I will generate high quality QA evaluation dataset for your rag system

Stop spending weeks hand-writing evaluation datasets for your RAG system.

I generate high-fidelity Q/A datasets from your own documents PDFs, DOCX, or URLs using a production pipeline built on Anthropic's Claude models.

WHAT YOU GET:

- Validated Q/A pairs extracted from YOUR documents

- Every pair filtered through a hallucination judge

- Multiple formats: JSONL, OpenAI fine-tune, HuggingFace

- Full provenance tracking

- Multi-lingual (English, French, Arabic)

HOW IT WORKS:

1. Send your documents (PDF, DOCX, URL list)

2. I run them through extract, chunk, generate, judge

3. You receive a clean dataset ready to use

USE CASES:

- RAG system evaluation

- LLM fine-tuning (OpenAI, Anthropic, HF)

- Domain-specific chatbot training

- Benchmark creation

WHY DIFFERENT:

Raw LLM output hallucinates and invents facts. My pipeline uses two-tier generation followed by a quality judge that rejects unfaithful pairs.

Message me before ordering to confirm your documents are a good fit.