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Lucius raises millions to put an AI in your group chat that learns by

May 19, 2026 | Source: qq | AI | 311 views 0 comments

Enterprise AI employee service provider Lucius has raised millions of dollars in an angel round led by Mingshi Capital. The startup's main product is an "Organizational Context Layer" that has already been deployed at over 30 companies. By logging and extracting real business decisions made by humans in chat apps like Discord and Feishu (a Chinese collaboration tool), Lucius claims to break the dependency of traditional RAG (retrieval-augmented generation, a common technique for grounding AI answers in existing documents) on manually configured knowledge bases.

Unlike plain RAG, which just retrieves documents to answer questions, Lucius is designed to remember every judgment call. When faced with an unknown question, instead of generating a likely-wrong answer, it routes the query to a human team. After the human responds, Lucius automatically extracts the scenario, risk boundaries, and follow-up actions from that reply. The next time a similar question comes up, the model can match with context, avoiding the trap of blindly applying old answers.

This approach has been validated across several communities. After AI dubbing tool Dubbing AI integrated Lucius, its Discord community's self-resolution rate jumped from 29% to 88% in one month, saving over 100 hours of repetitive answers. Low-code platform Momen.app also saw about 80% of queries handled autonomously. More importantly, these daily conversations are turned into callable corpus — product managers can directly ask Lucius about users' top pain points, using that data to drive iteration decisions.

Founder Zhao He previously led overseas-facing products like the no-code platform Zion. He found that the barrier to organizing business knowledge into a system is extremely high — customers are extremely reluctant to configure and maintain a knowledge base. Lucius's approach is to simply put the AI inside the chat, learning alongside humans, bypassing the cold-start problem entirely. The company also plans to shift from selling software tools to directly charging for business outcomes.

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