Yunyan Jiuchen Raises 10M Angel Round: Agentic OS Sector Heats Up
Another AI startup gets funding.
Yunyan Jiuchen, a 2026-founded AI brand, secured 10-million-yuan angel funding with its “white-box” Agentic OS (Autonomous Intelligent Operating System).
What caught my attention isn’t the amount, but the sector—Agentic OS.
This term is hot in investment circles, but honestly, most people (including me) didn’t initially understand what it actually is.
What Is Agentic OS?
Agentic OS isn’t an operating system—it’s an “agent orchestration platform.”
Simply put, its core functions are:
Task Decomposition: Breaking complex tasks (like “analyze this financial report and generate investment advice”) into multiple subtasks.
Agent Scheduling: Assigning appropriate AI agents to each subtask (financial analysis agent, risk assessment agent, report generation agent).
Result Integration: Combining outputs from various agents into final results.
Process Visualization: Letting users see what each agent is doing and why—this is “white-box.”
An analogy: Agentic OS is like an “AI project manager”—it doesn’t do the work directly, but handles task assignment, resource coordination, progress monitoring, and result reporting.
Why Is This Sector Suddenly Hot?
Gartner’s data tells the story: by end of 2026, 40% of enterprise applications will integrate task-based AI agents, compared to less than 5% in 2025.
What does this mean?
It means enterprise AI applications are upgrading from “point solutions” (like customer service bots, document assistants) to “multi-agent collaboration systems.”
Multi-agent collaboration needs an “orchestration layer” to manage—this is Agentic OS’s value.
Yunyan Jiuchen’s founder said something I find precise:
“Agentic OS isn’t an efficiency assistant, not a Copilot tool, but the enterprise’s ‘digital soul.’”
Sounds a bit mystical, but the logic holds: future enterprises will have dozens or hundreds of AI agents working simultaneously. They need an “operating system” to manage them—just like servers need operating systems today.
Ray’s Take: Agentic OS Solves AI Implementation’s “Last Mile”
Over the past two years, I’ve seen many enterprises attempt AI implementation, but all get stuck on the same problem:
Point AI tools (like customer service bots, document assistants) are easy to deploy, but hard to generate “systematic value”—because they’re isolated, can’t collaborate.
An example:
You equip the sales team with an AI customer assistant, finance team with an AI expense assistant, HR team with an AI recruitment assistant—but these three assistants don’t connect, data isn’t shared, processes aren’t coordinated.
Result: each assistant is useful, but overall company efficiency hasn’t significantly improved.
Agentic OS solves this problem: it enables different AI agents to collaborate, forming “systematic intelligence.”
This is AI implementation’s “last mile”—not point breakthroughs, but system coordination.
What Does Yunyan Jiuchen’s “White-Box” Mean?
Yunyan Jiuchen positions itself on “white-box” Agentic OS—its core differentiation.
What does this mean?
Traditional AI black-box models only show input and output—the intermediate process is opaque. Enterprises struggle to trust such systems, especially for decision-making scenarios.
“White-box” makes AI’s decision process explainable, traceable, and intervenable.
Specifically:
Explainable: Every agent’s actions and reasoning have clear logic chains.
Traceable: Complete decision logs for audit and review.
Intervenable: Humans can step in anytime to adjust agent behavior.
Why does this matter?
Because enterprise AI applications, especially in sensitive fields like finance, healthcare, legal, have extremely high requirements for “explainability.”
No matter how powerful black-box models are, enterprises won’t use them—because no one can explain what went wrong when problems occur.
White-box solves this pain point, letting enterprises “dare to use” AI.
A Small Detail: Yunyan Jiuchen’s Technical Path
From public information, Yunyan Jiuchen’s Agentic OS uses a “hybrid architecture”:
Bottom Layer: Based on open-source LLMs (DeepSeek, Qwen) with fine-tuning to control costs.
Middle Layer: Self-developed agent orchestration engine for task decomposition and scheduling.
Top Layer: Industry-specific solutions (finance, healthcare, manufacturing) providing ready-to-use agent templates.
This architecture is pragmatic: use open-source models at the bottom to reduce costs, do industry customization at the top to add value.
It also aligns with typical Chinese AI startup path: don’t compete on foundation models, compete on application layer.
The Controversy: Is Agentic OS Real Demand or Old Wine in New Bottles?
Some question: Isn’t Agentic OS just “AI orchestration tools”? Similar products existed before (LangChain, AutoGen), why is it hot again?
I think this criticism has merit, but misses a key change:
Before, AI orchestration required coding—developers using LangChain to build workflows, high barrier.
Now’s Agentic OS is “low-code or even no-code”—business users can use it.
This is like operating systems 20 years ago: initially only programmers could use them, then GUIs arrived and ordinary people could too.
Agentic OS is going through the same “democratization” process.
Ray’s Prediction: Agentic OS Is AI Implementation’s “Infrastructure”
2024-2025, AI entrepreneurship’s core opportunity was in “point applications”—build a useful AI tool, get funding.
Starting 2026, core opportunity shifts to “systematic integration”—how to make multiple AI tools collaborate to form systematic value.
Agentic OS is the infrastructure for this integration.
Yunyan Jiuchen’s 10-million angel round is just a signal—more funds will pour into this sector.
Gartner’s forecast data confirms this: global Agentic AI market size projected to grow from $7.29 billion in 2025 to $139 billion in 2034, 40.5% CAGR.
This is a sector with 20x growth over 10 years.
Final Thoughts
The heat around Agentic OS reminds me of cloud computing 10 years ago—also “infrastructure,” people thought it was far from money, but it became a battleground for giants.
AI agent infrastructure might follow the same path.
Yunyan Jiuchen is just the beginning. More players will enter.
(The End)