I will audit your rag system and reduce hallucinations


Über diesen Service
I will audit your RAG system and show you exactly where it fails with numbers.
I'm an AI engineer with 3 research papers and production RAG systems in healthcare, education, and sales. I built an open-source evaluation framework that scores 6 dimensions: faithfulness, hallucination rate, retrieval precision, answer relevance, context coverage, and a label-free confidence metric (UCM) that needs zero ground-truth labels.
WHAT YOU GET:
- Evaluation run on your real queries (OpenAI, Anthropic, Llama, or any provider)
- Hallucination rate + faithfulness scores, ranked by severity
- Root causes: chunking, retrieval, prompts, reranking
- Prioritized fix roadmap
Standard adds a full 6-dimension benchmark report. Premium implements the fixes and re-runs evaluation to show before/after numbers.
Works with LangChain, LlamaIndex, FastAPI, vector DBs (Pinecone, Chroma, FAISS, Weaviate).
Send your repo/docs and I'll start within 24h.
Lerne Sourav Roy kennen
AIML Engineer
- AusIndien
- Mitglied seitJuni 2026
- ⌀ Antwortzeit1 Stunde
Sprachen
Bengalisch, Hindi, Englisch, Italienisch

