CoreWeave Launches Serverless RL Platform, Revolutionizing AI Agent Development

CoreWeave woos enterprises with serverless RL suite

Because what enterprises really love are vague consumption-based pricing models Rent-a-GPU outfit CoreWeave continued its push into the AI services arena on Wednesday with the introduction of a platform that aims to make reinforcement learning more accessible to enterprise customers. Reinforcement learning (RL) is an approach to machine learning in which the model essentially teaches itself through trial and error by rewarding positive outcomes and penalizing negative ones. Over the past year, the approach has gained popularity as a means of fine tuning language models. For example, DeepSeek R1's ability to "reason" was achieved using RL. CoreWeave's Serverless RL platform, launched on Wednesday, builds on two of CoreWeave's most recent acquisitions: OpenPipe, which specialized in using RL to build custom AI agents, and Weights & Biases, which offers, among other things, a serverless platform for GPU-accelerated workloads. Serverless in this context makes a lot of sense because workloads can be distributed across available free or underutilized GPUs, eliminating resource stranding. Additionally, many AI workloads are inherently stateless, which means they don't need to store information from previous sessions in order to work. According to CoreWeave, this eliminates the need for customers to manually provision virtual machines or bare metal servers in order to build custom AI agents using RL. Instead, they only pay for the tokens generated as part of the fine-tuning process. If CoreWeave is to be believed, the approach is also nearly 1.4x faster and about 40 percent cheaper than using locally hosted Nvidia H100s. For the moment, CoreWeave is offering the service through the Weights & Biases platform. However, moving forward, the neocloud aims to extend its AI services business into new areas. Just this week, the company announced the acquisition of Monolith AI, which specializes in different kinds of AI. Instead of generative models, Monolith uses AI to accelerate what have traditionally been high-performance computing physics and engineering simulations. CoreWeave's push into the AI services business is part of a broader effort to diversify its customer base, which for better or worse has been dominated by larger hyperscalers, cloud providers, and model builders. When the company filed to go public earlier this year, it warned in its IPO prospectus that 77% of its 2024 revenue came from two customers, and no more than 10% came from any other single customer. The case is probably less stark now, with Google and IBM as customers, but nonetheless, diversification remains vital for the debt-saddled company. ®

CoreWeave stock rallies as it introduces new AI tools for developers

Michael Intrator, co-founder and CEO of CoreWeave participates in an interview on the floor of the New York Stock Exchange in New York on Sept. 22, 2025. CoreWeave shares rose as much as 8% Wednesday as the artificial intelligence cloud provider announced new tools to help programmers develop AI agents. With the new serverless reinforcement learning service, there's no need to worry about adding or removing computing power, because it happens automatically. Tests indicated that when developers use CoreWeave's new service, they can train models faster with 40% lower costs in comparison with running Nvidia H100 graphics processing units locally, "with no impact on model quality," according to a statement. Reinforcement learning is a decades-old approach that involves evolving systems through trial and error to improve outcomes over time. The launch comes five months after CoreWeave paid $1 billion to acquire Weights and Biases, a startup targeting developers with software for training and evaluating AI models. The deal is an effort to complement CoreWeave's existing business of renting out Nvidia graphics processing units to companies that need infrastructure to operate models.

CoreWeave stock rises on launch of Serverless RL for AI agent training By Investing.com

Investing.com -- CoreWeave, Inc. (NASDAQ:CRWV) stock climbed 8.6% Wednesday after the AI hyperscaler announced the launch of Serverless RL, a fully managed reinforcement learning capability for training AI agents. The new service allows developers to scale reinforcement learning across dozens of GPUs with minimal setup requirements, addressing historical barriers to entry like costly infrastructure and complex workflows. According to the company, benchmarks show nearly 1.4x faster training times and 40% lower costs compared to local H100 GPU environments. Serverless RL comes just weeks after CoreWeave's acquisition of OpenPipe, combining reinforcement learning tools with the Weights & Biases AI developer platform on CoreWeave's cloud infrastructure. The company stated that customers ranging from AI startups to Fortune 500 enterprises have already shown strong interest in the service. "We're excited about Serverless RL on CoreWeave to improve the quality of our agents, and eager for instant GPU access without the burden of managing infrastructure ourselves," said Jon Perl, CEO of QA Wolf, one of the early adopters. Earlier Wednesday, Evercore ISI analyst Amit Daryanani reiterated an Outperform rating and $175.00 price target on CoreWeave (NASDAQ:CRWV). The analyst commented: "We think it is worth revisiting the topic of unit economics for CRWV, especially given investor concerns surrounding profitability/business model following yesterday's Information article discussing the (low) profitability of ORCL's GPU cloud business. Despite the capex intensity/debt financing required to deploy GPU clouds, we view CRWV's model as durable, risk-managed, and profitable at scale even when taking high levels of depreciation expenses into account." This article was generated with the support of AI and reviewed by an editor. For more information see our T&C.

CoreWeave, Inc. Launches First Publicly Available Serverless Reinforcement Learning Capability to Build Reliable AI Agents

CoreWeave, Inc. announced the launch of Serverless RL, a fast and easy way to train AI agents using reinforcement learning (RL). The first publicly available fully managed RL capability, Serverless RL scales seamlessly to dozens of GPUs, requires only a Weights & Biases account and API key to get started, and delivers faster feedback loops with lower barriers to entry for developers. This new capability launches just weeks after CoreWeave's acquisition of OpenPipe, combining its leading RL tools with the Weights & Biases AI developer platform, powered by CoreWeave's AI cloud. reinforcement learning is critical to making AI agents more reliable, but it has historically been out of reach for most organizations. Running RL ordinarily requires access to costly infrastructure, deep expertise, and time-consuming workflows that slow down iteration. Serverless RL helps to remove those constraints so more enterprises can continuously improve AI agents and deliver a better customer experience. Benchmarks show nearly 1.4x faster training times and 40% lower costs compared to local H100 GPU environments, with no impact on model quality. This was achieved by solving the long-standing "straggler problem" in RL training. By multiplexing many training runs across CoreWeave's production-grade cluster environment, the system maintains high utilization in aggregate and only charges for incremental tokens generated. This delivers both improved throughput and significantly reduced cost in practice. Customers ranging from AI-native companies to Fortune 500 enterprises are already showing strong interest in Serverless RL. For example, SquadStack.ai, an AI-powered contact center platform that delivers hyper-personalized experiences for leading consumer brands, will use Serverless RL to enhance customer engagement. As will QA Wolf, a hybrid platform that helps technology teams ship better software faster.