CoreWeave (CRWV.US) Double Launch in One Day: Physical AI Workload Templates and Zero Trust Security Framework Debut Simultaneously at GTC Berlin, Premarket Shares Rebound Over 2%

On Wednesday, AI cloud service provider CoreWeave (CRWV.US) launched two products at NVIDIA Corporation's (NVDA.US) GTC event in BerlinPhysical AI Launchables for Siasun Robot&Automation and autonomous driving, and the Zero Trust AI Framework for the agentic AI era. Following the announcement, as of press time, CoreWeave's premarket shares rose more than 2%, providing temporary relief after a deep drawdown of over 25% last week. The two launches may point to a single strategic intent: CoreWeave is attempting to extend itself from a pure "compute supplier" toward the physical AI engineering layer and security control layer, occupying a position closer to customer workflows within the NVIDIA Corporation ecosystem. Physical AI Launchables: Compressing "the pain before running" into a single command Physical AI Launchables is not positioned as a new compute product or model tool, but as a set of workload templates built and tested by CoreWeave engineers. Siasun Robot&Automation, autonomous driving, and simulation teams can launch tasks with a single command, without having to rebuild environments, configure storage, and wait for schedulers to be ready before every run. Richard Ahlfeld, Senior Vice President of Physical AI at CoreWeave, said: "Siasun Robot&Automation and autonomous driving teams are doing some of the most demanding engineering work in this industry, and they should be spending their time on that. Physical AI Launchables provide a tested starting point for the tools they are already using." The first batch of templates covers five tools: NVIDIA Isaac Sim, CARLA, MuJoCo, NVIDIA AlpaSim, and NVIDIA Cosmos 3, spanning three key stages of the physical AI loop: data generation, evaluation and scoring, and policy training. In addition, Launchables integrates agent skills from Cosmos Data Factory for generative data augmentation, automatic labeling, data curation, and retrieval across video, images, and text; each template also comes with optimized skills for coding agents such as Claude Code and Codex, enabling agents not only to "launch a run" but also to read run outputs and judge whether the results are useful. Notably, each tool also comes with a blank template, so teams are not confined to CoreWeave's pre-packaged workloads and can point to their own scenarios and data on the tested foundation. Nakul Arora, Director of Product Management at NVIDIA Corporation, said that NVIDIA Corporation's reference agent skills for physical AI are designed to run on any cloud, while CoreWeave has built its own version optimized for its AI cloud, enabling these workflows to "run natively on its infrastructure." Zero Trust AI Framework: Six layers of protection, keeping CoreWeave "outside the chain of trust" The Zero Trust AI Framework released the same day directly addresses the security paradigm shift brought by agentic AI. When AI agents retrieve context across multiple systems, invoke tools, and trigger actions, sensitive data no longer stays within a single application boundary but travels among prompts, embeddings, model weights, run traces, and outputs. Under the traditional cloud model, customers have had to extend trust to cloud service providerswith providers managing encryption keys, holding privileged server access, and even operating proprietary models that may learn from customer interactions. Chen Goldberg, Executive Vice President of Product and Engineering at CoreWeave, said: "Security for AI workloads cannot depend on a provider's promise about its own behavior. The Zero Trust AI Framework replaces assurances with architecture, keeping critical control in customers' hands." According to the introduction, the framework consists of the following six layers of protection: Zero Key Access: Through remote key encryption, customers continue to use their existing key infrastructurewhether software key managers, hardware security modules, or KMS deployed on other cloudsand key control does not transfer; Zero Node Access: Support for access management makes provider access an explicit customer decision, with customers authorizing access within defined scopes; Zero Trust Infrastructure: Establishes verifiable trust at the infrastructure layer based on a hardware root of trust; Zero In-Use Access: Plans to extend NVIDIA Corporation's third-generation confidential computing to CPUs and GPUs, covering data in use, with the relevant capabilities to land with HGX Rubin NVL8 in the fourth quarter; Zero Model Data: CoreWeave explicitly does not train its proprietary models on customer data; Zero Trust Network Encryption: Uses MACsec backbone encryption to secure inter-node communications. CoreWeave summarizes the overall design goal as "keeping itself outside the customer's chain of trust"security no longer depends on provider promises but is delivered through customer-held keys, access authorization, and encryption architecture. In addition, CoreWeave said it intends to use NVIDIA Corporation's NVLink interconnect technology, including Nvidia HGX Rubin NVL8 for its confidential computing, and HGX Rubin NVL8 will launch in the fourth quarter. Stock price backdrop: Rebound after deep drawdown, divergence remains The two launches come at a point of sharp volatility in CoreWeave's stock price. Over the past week and a half, the stock has fallen more than 20% cumulatively, triggered by concerns over its roughly $50 billion debt burden, credit default swap spreads briefly reaching distressed levels, and Tesla, Inc. CEO Musk's "yikes" on social media amplifying market sentiment. But Wall Street analysts have not formed a consensus bearish view: Bank of America reiterated its "Buy" rating and $140 price target the day before the launch event, arguing that CoreWeave's core advantage lies in "bringing active power capacity online at scale and speed," and that its five-year major customer contract structure provides high revenue visibility. In contrast, HSBC maintained its "Underweight" rating and $39 price target, citing the company's expected return on invested capital averaging about 8.9% from 2026 to 2030, below its borrowing cost, and arguing that "the more it invests, the more value it destroys." LSEG data shows that of the 45 analysts covering CoreWeave, 32 still give "Buy" or "Strong Buy" ratings, with HSBC's view in the minority. Against this backdrop, the simultaneous release of Physical AI Launchables and the Zero Trust AI Framework provides CoreWeave with new material that goes beyond the "debt and compute" narrative to some extent: the former points to competition for the entry point of physical AI workflows, while the latter responds to enterprise customers' most sensitive concern about security control in scaled agent deployment. Whether the two products can verifiable revenue and customer retention may become the core test for the market in the future.