Lune - AI Agent Grounding for Scientific Research

AI agents often hallucinate or misuse research when working on scientific problems. Lune provides an MCP server that grounds AI agents with verified research literature and best practices from scholars. Target users are researchers, universities, and organizations using AI for scientific discovery.

The push toward agentic AI workflows in 2024-2025 has exposed a real problem: LLMs confidently cite retracted papers, misattribute findings, and fabricate methodology when operating autonomously on scientific tasks, and institutions are starting to notice the liability. No clear incumbent owns the MCP-layer grounding space specifically for scientific literature, though Semantic Scholar and Elsevier's AI tools operate adjacent and could expand here. The $2k-10k/mo revenue band is plausible for a narrow SaaS wedge selling to labs and universities, but those buyers have long procurement cycles and tight budgets, which makes that ceiling realistic rather than conservative. The biggest risk is that frontier model providers — OpenAI, Anthropic, Google — bake citation-grounded retrieval directly into their APIs, collapsing the differentiation before any meaningful customer base is established.