Creao AI's 'Better Loop' Nabs $10M to Turn Conversations into Autonomous Workforces

CUPERTINO, CA – April 17, 2026 – While most AI startups are racing to build a better model, Creao AI is betting its future on a better loop. The company today announced a $10 million funding round led by Prosperity7 Ventures, the diversified venturing fund of Aramco Ventures. The investment brings Creao AI’s total funding to $25 million in under a year and validates its ambitious mission: to close the gap between a chatbot answering a question and an autonomous agent running your business while you sleep.

“Everyone knows AI promises an explosion of productivity,” says CEO Kai Cheng, who spent a decade building production AI systems for enterprise clients before co-founding the company. “But the industry is stuck in two traps. If humans still operate AI tools step-by-step, productivity hits a ceiling. And if humans are still the only ones building the tools, the real AI revolution hasn't even started.”

Creao AI’s solution is a radical departure from conventional AI tools. It’s a closed-loop system where artificial intelligence not only executes tasks but also builds the tools to do them, creating a reality where one person can manage workflows that previously required an entire team.

Beyond Chatbots: The 'Closed-Loop' System

At the heart of Creao AI’s platform is what the company calls a “super agent.” A user starts with a simple conversation, describing a complex task like launching a marketing campaign or running an SEO analysis. The super agent doesn't just provide a plan; it executes it. It writes code, calls APIs, connects to other software, and delivers the results in a secure, sandboxed environment.

The true innovation is what happens next. A successful workflow isn't a one-off event. It is saved as a reusable “Agent App”—a persistent, schedulable unit of automation complete with its own memory. This means the SEO pipeline you designed on Tuesday can be set to run again every Friday, automatically, without any further human intervention. This architecture is designed to break two key constraints: the “builder bottleneck,” by allowing AI to create tools via conversation, and the “operator bottleneck,” by enabling AI to run those tools autonomously.

The platform is built on three distinct layers: a Coding Agent that builds the tools, an Autonomous Execution layer where Agent Apps run on schedule, and a Workspace where humans orchestrate the entire system. “If AI builds a tool but a human still has to click 'run' every time, we haven't won,” Cheng explains. “The whole point is a closed loop: AI builds it, AI runs it, humans steer.”

A Crowded Market, A Different Bet

Creao AI enters a blistering hot market. The AI agent sector is projected to swell to $52 billion by 2030, and venture capital is flowing freely. Recent months have seen Meta acquire the general-purpose agent Manus for a reported $2 billion, while Genspark, an AI workspace, hit a $1.25 billion valuation. Meanwhile, competitors like Gumloop and Relevance AI have raised significant rounds for their agent-building platforms.

However, Creao AI is making a fundamentally different bet. Where Gumloop offers a no-code, drag-and-drop canvas and Relevance AI provides pre-configured agent teams, Creao AI bypasses the visual builder entirely. There is no canvas of nodes to connect or a marketplace of templates. The platform’s core philosophy is “conversation-to-infrastructure.” You talk, the agent works, and the successful result becomes a durable, automated asset.

“Everyone else is building better ways to instruct AI,” Cheng says. “We're building the layer where AI work compounds—where every run feeds memory into the next, and successful work becomes an app that runs itself.” While Genspark focuses on deep research and synthesis for knowledge workers, Creao AI is aimed at automating recurring business workflows. While Manus proved a single powerful agent can perform complex tasks, Creao AI aims to make that power persistent and repeatable.

Forged in Failure: Five Pivots and an Execution Moat

The company’s current clarity was hard-won. The founding team has navigated five major pivots since its inception in mid-2024. After launching as a “vibe-coding tool” in September 2025, they scrapped the initial product and rebuilt it around the super-agent thesis. This journey of trial and error has become central to their strategy.

Creao AI practices what it preaches, using its own 20-person team as “crash test dummies for the future of work.” The company runs its own marketing, SEO, and content production pipelines on the CREAO platform. In one instance, a single agent replaced a three-person SEO workflow overnight. In another, an autonomous content agent ran for two days producing unusable output before a human noticed—a failure that immediately informed the product’s monitoring features.

“Every internal failure becomes a product insight,” Cheng states. “Every broken workflow becomes a feature spec.” This relentless internal dogfooding supports his belief that in the current AI landscape, the only defensible advantage is execution. He draws an analogy to hardware manufacturing, where supply chain efficiency, not just design, creates a structural advantage. “For AI startups, there is only one true strategic advantage: who can adopt AI first, internalize it, and use it to multiply their own efficiency by 100x.”

The People Behind the Agents

This intense focus on execution is backed by a team with serious technical credibility. CTO Peter Pang was a research scientist on Meta’s influential Llama 3 team and previously worked on multimodal models at Apple. Pang’s conviction is that AI will change the very nature of engineering work. “The value of an engineer is no longer measured by how much code they type,” he wrote in a recent company memo. “It is measured by clarity of thinking and quality of decisions.”

This philosophy, combined with the go-to-market experience of co-founder Clark Gao, who previously built data teams at LinkedIn and Tencent, has shaped a company culture built for speed and adaptation. The team’s journey through multiple failed concepts, Gao notes, was a necessary process to dig deeper into the fundamental problem of how humans and AI can work together most effectively.

Investors are taking note of this unique combination of vision and execution. “As AI adoption matures, the focus is shifting from models to execution,” said Raed Twaily, Executive Managing Director at Prosperity7 Ventures. “Creao AI is building the infrastructure layer that allows agents to operate autonomously, reliably, and continuously.”

The new funding will be used to expand the engineering team, deepen enterprise integrations, and scale the platform’s capacity for agent-to-agent collaboration. With 200,000 users already acquired through organic adoption alone, the company is poised to capitalize on its unique position. As Cheng puts it, the goal is simple but profound: “When you combine AI's ability to build tools, its autonomy to run them, and a workspace designed for human orchestration, you create a reality where one person can accomplish what previously required a team.”