Zhiman Technology
AI company pioneering industry-specific large language models to revolutionize semiconductor manufacturing through intelligent, model-driven solutions.
| Date | Investors | Amount | Round |
|---|---|---|---|
* | CNY20.0m | Seed | |
| Total Funding | 000k | ||
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Zhiman Technology, founded in 2024, is a technology firm specializing in industry-specific large language models (LLMs) for the semiconductor sector. Headquartered in Beijing, with an office in Shanghai, the company aims to drive the artificial intelligence transformation of the semiconductor industry. In May 2025, Zhiman Technology secured CNY 20.0m in a seed funding round from Hua Capital.
The company's core business revolves around providing a comprehensive LLM ecosystem solution for semiconductor enterprises, addressing challenges in research and development, efficiency, and productivity. The business model appears to be B2B, offering software-as-a-service (SaaS) subscriptions. Zhiman Technology's platform integrates multimodal datasets, vertical domain-specific models, and private deployment tools. This enables semiconductor companies to adopt AI-powered workflows for process optimization and defect analysis without relying on general-purpose models. The company has constructed an extensive multimodal knowledge base for the semiconductor industry, which includes data from process technology, scientific research papers, and equipment-side data.
Zhiman Technology offers a suite of specialized models, including Zhiman-Rag for information retrieval, Zhiman-Code for generating equipment scripts, and Zhiman-Semi, which is trained on industry knowledge to answer technical questions. They also provide multimodal models like Zhiman-Semi-VL for visual information recognition and Zhiman-Semi-on-Device for real-time equipment maintenance assistance. The platform features capabilities for building enterprise-level knowledge bases, intelligent code assistance, and AI-driven search that can extract answers from technical documents. By focusing on specific applications within semiconductor design, parameter adjustment, and coding, the company has demonstrated validated use cases that reduce the burden on engineers and improve design efficiency and production yield.
Keywords: large language models, semiconductor manufacturing, artificial intelligence, B2B, SaaS, deep tech, enterprise software, process optimization, defect analysis, intelligent manufacturing