Eagle Cloud, an AI security governance infrastructure provider, today announced it has closed a Series B+ round of close to RMB 100 million (approximately USD 14 million), just four months after its Series B. The round was co-invested by MTR Lab and Northern Light Venture Capital, with Voyagers Partners serving as financial advisor.
This marks Eagle Cloud's second funding round in just four months, reflecting investors' continued confidence in the AI governance space and strong recognition of the company's product capability, commercial progress, and global growth potential.
The funding will go toward two priorities:
- Extending Eagle Cloud's governance infrastructure to keep pace with AI agents and other new categories of autonomous action inside the enterprise
- Accelerating international expansion, building on its existing overseas business with a larger overseas team, deeper market development, and stronger local delivery capability
Trust Is the Precondition for AI to Act
AI is moving from answering questions and assisting decisions to becoming an agent that acts on its own and executes tasks. Agents like Claude Code, Codex, and WorkBuddy have already entered enterprises' day-to-day workflows: R&D, production, sales, operations. Enterprises now have to answer a new set of questions: what is an AI allowed to do, who does each agent belong to, what resources can it access, what actions can it take, when should it be restricted or stopped, who is accountable if something goes wrong, and how are inputs and outputs measured?
The agents are here. The trust isn't. For enterprises to confidently grant AI the power to act and scale its use, they need governance infrastructure that matches what AI agents can now do, extending the scope of governance from people alone to people and AI together. Trust is the precondition for granting AI that autonomy at scale.
Built on Eagle Cloud's own proprietary unified platform, Yunshu, the company puts this governance principle into practice: govern every actor inside the enterprise, human and AI, under one system. Yunshu AIDR (AI Detection & Response) governs an agent across its full lifecycle, from creation to retirement, through five steps: Discover, Define, Identify, Enforce, Measure.
- Discover — Solves the problem of AI asset visibility: automatically finds every agent and related configuration across the enterprise, building a live, continuously updated map of what AI exists and bringing "shadow AI" into governance scope.
- Define— Brings governance forward to the design stage: sets an execution contract for each type of agent, spelling out its task objectives, role and responsibilities, permission boundaries, validity period, and cost budget.
- Identify — Solves the problem of agent identity and accountability: assigns every agent a unique identity, tied to its creator, user, and owner, so it's always clear who initiated it, who authorised it, who executed it, and who's responsible.
- Enforce — Continuously checks an agent's actual behaviour against its execution contract, flags permission violations and anomalies, and applies alert, restriction, or blocking measures based on risk.
- Measure — Tracks AI resource costs by model, agent, workflow, and owner, tied to outcomes, giving enterprises a quantified basis for budgeting, performance review, and resource planning.
HU Min, Co-Founder and CEO of Eagle Cloud: "Every leap in productivity creates the need for new management infrastructure. Whatever comes next, no matter agents working across or between organisations, or physical AI that can sense and act on the real world, they will need governance that matches what it's capable of. Eagle Cloud's long-term vision is for every organisation run by people and AI together to be built on verifiable trust."
Existing Control-Point Coverage: Eagle Cloud's Structural Advantage
AI governance requires new capabilities, but enterprises aren't implementing it from scratch. Once agents enter the enterprise, they connect to identity, endpoints, network, applications, and data. Governance must reach into those same layers.
Eagle Cloud's first advantage is its existing control-point coverage across real business environments. The company already serves 1,000+ enterprises across 20+ industries, covering more than 5 million endpoints, and has integrated the key governance layers (identity, endpoint, network, application, and data) on the Yunshu platform. Built on these existing control points, Yunshu AIDR can discover AI assets, define governance boundaries, and enforce governance policy within an enterprise's current architecture, moving AI governance to scale faster with less fragmentation, less duplicated build-out, and less long-term operational burden.
The second advantage is that operating at scale keeps its governance capability evolving. As AI governance is deployed across more industries and business scenarios, Eagle Cloud continually builds up governance methods, risk patterns, and operational experience, feeding that back into product and governance-model improvements: a positive flywheel of scale, experience, and capability.
Eagle Cloud is now applying the product capability and governance experience it has built across complex Chinese enterprise environments to accelerate its expansion into international markets.
Hong Kong as the Pivot for Global Expansion
Eagle Cloud has long seen Hong Kong as its base for international expansion and was among the first companies admitted to the Hong Kong-Shenzhen Innovation and Technology Park (HSITP), in the AI and Data Science track. With the support of HSITP and its ecosystem partners, Eagle Cloud connects with market resources across Southeast Asia and Central Asia, helping it expand into global markets.
For enterprises in Hong Kong and other international markets, AI governance maps directly onto regulatory expectations alongside the technical questions it raises. Eagle Cloud's unified record of actions, authorisation, and accountability across people and AI gives enterprises a verifiable basis to respond to that scrutiny.
Focusing on smart city and sustainability-related sectors, MTR Lab is committed to driving the scalable growth of deep tech companies while emphasising AI infrastructure and security governance capabilities. This aligns with Eagle Cloud’s vision of adding unique value to enterprise customers looking to deploy AI effectively and safely in embracing the AI era. MTR Lab’s investment in this round is anticipated to help Eagle Cloud deepen its presence in Hong Kong, Macau and Southeast Asia, while further expanding into broader overseas markets.
Investors Perspectives
MTR Lab: "As AI continues to be integrated into enterprise business processes, demand for integrated cybersecurity governance capabilities continues to grow. Eagle Cloud has demonstrated solid growth potential in the AI governance space through its ongoing technological innovation, mature enterprise-grade products, and ability to address real customer pain points. Through this investment, MTR Lab hopes to support Eagle Cloud in further enhancing its technology solutions and expanding its overseas service capabilities, enabling broader market adoption."
Northern Light Venture Capital: "AI is becoming a core part of enterprise productivity, and the governance needs that come with it are emerging fast. Eagle Cloud has a clear first-mover advantage and a strong track record of innovation in this space. We believe it's well positioned to capture both the AI shift and the wave of Chinese enterprises expanding overseas, and to grow into a globally competitive company."
