Startup Clay raises $115 million to build AI sales teams in B2B sector

Engineers have long faced a problem: artificial intelligence capable of writing novels in seconds struggles to grasp fragile glass without crushing it. This issue stems from a significant gap between digital intelligence and physical execution.

Bridging this gap requires flawless and continuous feedback between software systems and mechanical bodies. To solve this narrow problem, Kinetix AI has secured $75 million in a major and significant angel funding round, marking a serious step forward in embodied intelligence.

The historic funding round was led by Vertex Ventures, the powerful venture arm of Singapore's Temasek Holdings. F&G Venture and Wanshi Capital also joined the round to invest over 500 million RMB (approximately $75 million) in the early-stage startup, Kinetix AI.

Kinetix AI is not a small garage project. Founded in September 2025, the company has rapidly grown to nearly 200 employees. Driving Kinetix AI's rapid growth is CEO Yu Ze, who previously commercialized autonomous mining trucks for Huawei.

The team also includes Luo Ping, an outstanding deputy dean from HKU, and Zheng Qunyuan, former head of robotics at XPeng. This group possesses deep knowledge combining academic theory, autonomous vehicle logic, and manufacturing capabilities.

Many robotics companies cut corners on quality, but Kinetix does not accept this. The company firmly believes that since the world's infrastructure is built for humans, robots must look and move exactly like us to integrate seamlessly.

Their flagship creation, KAIBot, stands 1.73 meters tall and boasts an impressive 115 degrees of freedom. It is distinguished by its high quality and ultra-realism. Although creating such a robot requires significantly higher initial costs, and the supply chain is a nightmare, co-founder Zheng Qunyuan argues that starting with cheap, low-quality equipment is simply foolish. By locking down a true human form factor, they ensure their AI models will not fail as soon as any joint is updated.

Imagine a robot that doesn't just mimic the human silhouette but perfectly matches human motion data. When the hardware directly reflects our biology, algorithmic work transfers effortlessly.

The core magic happens thanks to the attracted capital, which is directed towards accelerating their closed ecosystem. This can be visualized as a three-headed monster. First, it involves collecting multimodal, egocentric data. Then, this raw data is fed directly into the native fundamental model embodied in the body. Finally, hardware such as KAIBot and the highly maneuverable KAI Hand physically executes the learned actions.

This continuous loop creates an 'intelligence flywheel.' As the robot collects sensory data from the real world, the AI model becomes smarter, instantly enhancing the capabilities of the physical hardware. There is no longer a need to rebuild the physical machine with every software update.

The system's dynamism was demonstrated at the 2026 World Games for Human Robotics, where their system played table tennis against world champion Ding Ning. The goal is to create a premium class of robots ready for complex real-world tasks.

Amid growing demand for software and a shortage of engineers who hinder teams from completing features, fixing vulnerabilities, and updating systems, Cognition has introduced a solution based on AI coding tools. The core idea is to allow engineers to act as architects while artificial intelligence agents perform the actual coding, testing, and deployment.

Cognition AI successfully raised $2 billion in a Series E round. The round was led by new investors Andreessen Horowitz and Accel, with participation from existing partners including Founders Fund, General Catalyst, and Avenir.

Cognition's annual revenue increased from $492 million in May to nearly $900 million currently. The startup has developed Devin—an autonomous software development agent capable of planning, writing, testing, and deploying code with minimal human involvement.

Devin differs from simple code auto-completion tools like Copilot because it operates based on high-level requirements. The user only needs to give a command, such as 'fix this bug' or 'create this function.' Devin independently determines the necessary steps, writes the code, verifies it, resolves any shortcomings, and then deploys it to a secure test environment.

Recent feature additions include Devin Auto-Triage for analyzing production incidents, Devin Security Swarm for finding code vulnerabilities, and Devin Automations, which runs agent tasks via Slack, GitHub, and Linear.

Large corporations are already using the product. Cognition's clients include Nvidia for chip design, GE Aerospace in the aviation industry, Citi in financial services, Mercedes-Benz in the automotive industry, and Goldman Sachs. Since the system is not tied to one AI company, it can select the most suitable AI 'brain' for a specific task, whether it be OpenAI, Anthropic, or Cognition's own development. Engineers focus on design and verification, while agents handle execution.

Scaling AI coding requires significant expenditure, as Cognition leases a large number of Nvidia chips, costing them hundreds of millions of dollars annually. Experts predict that the company's expenses could reach $800 million just in 2026. To address this, Cognition is training its own model based on open-source alternatives, aiming to reduce dependence on expensive third-party models and approach the break-even point.

The company is also expanding Devin's capabilities and entering new markets. Annual revenue is expected to reach $4–5 billion by the end of 2026. The growing demand for software is driven by AI development: every company needs AI features, but implementing them requires code, creating a closed loop where AI needs more software, and software needs more AI for writing. Cognition is betting that this cycle is so massive that it can support several $50 billion companies.

CEO Scott Wu's vision is for engineers to transform into AI agent managers. Instead of writing every line of code, they will focus on verifying, directing, and approving it. If this model proves successful, the potential for software creation globally could multiply, allowing for faster security fixes and launching startups in weeks instead of months.

Having reached a $48 billion valuation, Cognition has become another giant in AI coding. Four months ago, its valuation was $26 billion, and it could grow even more by next year. Investors are clearly betting that the future of software lies not in one AI, but in many, and that coding will become the first task AI can truly automate at scale.

Creating artificial intelligence infrastructure today requires enormous initial capital investments, as maintaining servers is extremely costly. This significant financial burden often prevents most ambitious startups from launching.

However, the situation is changing: VAST has successfully raised $446 million (equivalent to three billion yuan) in a rapid Series B and B+ funding round. This makes the company one of the largest players in the generative 3D space, causing noticeable shifts across the entire market.

For a long time, the development of immersive three-dimensional digital worlds has been slow and expensive. The reason lies in the fact that generative 3D differs from creating flat, two-dimensional images; it requires more than just predicting the next pixel in a grid.

It involves spatial computing, complex geometric shapes, meticulous lighting modeling, and interactive physics. The required computational power is staggering, and the cost of graphics processing units (GPUs) continues to rise. This growing cost barrier has historically excluded small creators and independent developers from the high-quality content generation process because they could not afford the entry ticket.

Major industry players are beginning to recognize this bottleneck problem and, instead of backing away, are directing significant funds toward finding solutions. Matrix Partners China led this process, but it was not acting alone. The volume of industrial capital invested in this round proved to be substantial.

Perfect World, BlueFocus, and 37 Interactive Entertainment joined them, as they understand that the entertainment and gaming sectors are in urgent need of revolutionary changes. Creating complex 3D content for games usually takes hundreds of hours of manual labor. If a sophisticated AI model can generate a fully textured and rigged 3D character in just a few seconds, it will lead to an explosive increase in profit.

The financial syndicate is supplemented by major investors such as CICC Capital, CDH VGC, and CMC Capital Partners. Existing shareholders also actively participated in the subscription, aiming to maintain their stake. In less than six months, VAST has raised about five billion yuan, an unprecedented figure for the 3D AI sector.

Capital always flows where the friction is highest. Currently, this friction is concentrated in the 3D production pipeline. With such a significant reserve of funds, VAST is not just trying to survive the AI hype cycle; the company is poised to dominate it. A radical acceleration of rendering time and deeper integration of physical models are expected.

Essentially, there is a complete transformation in how people create virtual environments from scratch. Examples include modern virtual reality applications and next-generation video games, which require an infinite amount of 3D assets to fill vast digital spaces. Manual creation of such elements is no longer a viable option. VAST has acquired the resources to build a powerful mechanism that brings these assets to life.

The implications of this event are massive. When a company accumulates such a volume of engineering talent and computational power, competitors are forced to either adapt or disappear. It is likely that many accelerated 3D prototyping tools will enter the market next year. Smaller startups will either pivot to niche applications or seek favorable acquisition offers. This is not just a successful funding round, but a loud and aggressive shift in the industry.