Deep Research Agent with a separate review layer: Nemotron researches, Jev judges
blaizedsouza · x · 2026-10-21
A developer built a deep research agent where NVIDIA Nemotron (via Nebius Token Factory) does research and writes cited reports, Tavily handles web search, and Jev acts as a separate review layer deciding whether the research is good enough to return.
The workflow: research → draft → Jev review → another research pass if needed → final answer. The key idea is separating the model doing the work from the model judging whether that work is complete, instead of asking one LLM to generate, verify, and self-approve. Based on Nebius's modular deep-research blueprint, with orchestration, inference, retrieval, evaluation, and tracing as replaceable parts, and a Streamlit UI showing plans, sources, review outcomes, and LangSmith traces.
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