About · Zhiway
Build the knowledge environment
research agents are missing
Zhiway builds agent-native research knowledge infrastructure and knowledge commercialization capabilities for model providers and research institutions. We focus on the stage before experiments begin: as AI lets laboratories pursue more directions in parallel, the scarce decision shifts from how to run experiments to which routes deserve to begin.
The endgame is a closed Discovery Loop. The human role will increasingly concentrate before an experiment begins: constructing a direction, checking evidence, and judging feasibility.
Why we exist
Large models can read papers, but they do not naturally preserve citation structure, field evolution, or the research state already tested, rejected, and redirected. The missing layer is a trusted, traceable, stateful external knowledge environment that updates faster than model-training cycles.
Idea Network organizes this environment; Idea Interflowing turns it into pre-experiment judgments; Research Claw and Research FDE then enter institutional settings and adapt general capabilities to concrete, testable tasks.
How we named ourselves
The Chinese name 清智万维 carries three characters: Qing, from Tsinghua University; Zhi, for artificial intelligence; Wanwei, the world-wide web of ideas, citation networks and creative connections. Together they capture exactly what we care about most: using an academic pedigree and the power of agents to accelerate how ideas flow and collide across the citation network.
Where we're headed
We begin by making the pre-experiment boundary of inquiry trustworthy. Human and agent decisions then accumulate as process data; mature knowledge environments and institutional workflows can ultimately connect to broader experimental execution and research-output commercialization.
Journey
From real delivery to a shared knowledge layer
A 2024 research service proved demand and exposed the delivery ceiling. Successive SaaS and local-agent products then pointed to the same structural bottleneck: research agents need a trusted, stateful knowledge environment. That insight became Idea Network and now enters institutions through Research FDE.
Team
Covering precisely every capability this work demands
First-hand research experience, multi-agent engineering, and a channel into institutional and international markets — a team that holds all three at once is, in itself, a scarce asset.
Siyuan Liu
Founder · CEO
- MSc in CS / AI, University of Southampton; large-model algorithm expert
- 10+ years bringing AI applications to production; five products built solo
- Led the development of China's first medical LLM and a financial-research LLM
Haonan Zhang
CSO · Chief Strategy Officer
- PhD and Shuimu Scholar; Assistant Researcher, Institute for AI International Governance, Tsinghua University
- Member of the Academy of Management (AOM)
- 7 papers in leading international journals and 4 at top conferences; national gold medal at the Challenge Cup
Yilong Li
Co-Founder · Head of Engineering
- Tech lead for the Xiangyu product line at 5i5j Group
- SaaS expert and full-stack Java web engineer
- Has co-founded LLM and agent startups with Siyuan Liu since 2023
Fei Meng
Co-Founder · Head of Operations
- Honours BEng in Engineering, University of Adelaide, Australia
- Project manager at Stantec; five years of full-lifecycle project management in international consulting
- Delivered projects with a combined budget of over AUD 10 million; leads strategic partnerships across Asia-Pacific
Xueqi Zhao
Head of University–Industry–Research Partnerships
- Digital and AI policy expert at the United Nations Industrial Development Organization (UNIDO)
- PhD; Assistant Researcher, School of Economics and Management, Tsinghua University
- Has led national and provincial/ministerial projects and published 15 high-level papers; gold medal at the National Innovation & Entrepreneurship Competition
Jinghui Yin
Head of Investment & Financing Partnerships
- PhD; Assistant Researcher, School of Economics and Management, Tsinghua University
- 10 high-level papers published
- Five research reports received high-level endorsement or adoption
With the help of Zhiway's system, researchers have authored and put their own names to papers that have earned 3 acceptances at IJCAI, EMNLP and AAAI, with a fourth under review — and blind review at top conferences is the harshest third-party test this field has.
Let agents see how the literature connects
Use a knowledge environment to support pre-experiment decisions, then bring it into institutions through Research Claw and Research FDE so every judgment has evidence and every redirection preserves state.
Start experiments without betting blind.
Research Knowledge Environment
Pre-experiment Research Decisions
Institutional Field Delivery
FAQ
About Zhiway
What kind of company is Zhiway?
Zhiway builds agent-native research knowledge infrastructure and research-output commercialization capabilities for model providers and research institutions. Models provide general intelligence; Zhiway organizes literature relationships, source evidence, and research state, then adapts them to real institutional workflows through Research FDE.
What does the name "Zhiway" mean?
In Chinese, the name 清智万维 reads as: Qing, from Tsinghua University; Zhi, for artificial intelligence; Wanwei, the world-wide web of ideas, citation networks and creative connections. The English name Zhiway echoes "the way of intelligence."
What products does Zhiway build?
The current system consists of Idea Network, Idea Interflowing, Research Claw, and Research FDE: respectively the research knowledge environment, pre-experiment decision workspace, local institutional agent environment, and field adaptation method. ThesisAgent and HashMind are previous validation products scheduled to stop maintenance on September 1, 2026.
How is Zhiway different from other AI for Science companies?
General models provide intelligence; Zhiway provides the open-book research environment. Idea Network preserves literature relationships, source evidence, and research state outside the model, while researchers retain responsibility for direction, evidence review, and final judgment.
How can I contact Zhiway?
Email us at contact@zhiway.com.cn.
Walk with us
Whether you're a researcher, an institution, or simply someone who cares about AI for Science — we'd love to hear from you.