CoreWeave (CRWV) signs multi-year deal to power Harell Data's private biotech AI training platform

CoreWeave logo

Key points

  • A multi-year deal with no dollar figure disclosed
  • Harell says raw datasets stay inside its platform
  • Harell says data owners earn a share of each training job
  • The GPUs are Nvidia A100 and Hopper chips

CoreWeave (CRWV) signed a multi-year deal to power Harell Data's platform for training AI on private biotech datasets, the companies announced Wednesday. Harell says developers can train models on its platform without seeing or extracting the underlying data.

The agreement covers training, fine-tuning and inference on CoreWeave's cloud. The companies disclosed no contract value, exact duration or computing capacity, and named no data providers or model builders using Harell's platform.

CoreWeave shares traded at $87.17 in premarket trading as of 8:57 a.m. Eastern time Wednesday, up about 0.5% from Tuesday's $86.76 close.

How the platform works

Harell's approach is to bring the model to the data. Training runs execute inside Harell's platform on Nvidia (NVDA) A100 and Hopper GPUs, and the raw data never leaves it, according to the release. What the model builder takes away is the trained model and the rights to sell it.

Harell meters compute for each training run, and the owner of the dataset earns a revenue share on every job run against it. Builders can then list their models on the Harell marketplace and collect a fee each time someone uses them. Harell calls this arrangement Models as a Service.

Testing follows the same separation. Harell's data partners keep the test questions hidden, so no builder has seen the answers, and every result is published against one standard, the release says.

Harell describes itself as a platform for training on proprietary data "in biology and beyond," with biotech datasets as the starting point. The company is based in Bellevue, Washington, and was founded by Harlan Robins, a co-founder of Adaptive Biotechnologies.

"We created Harell Data to connect researchers to proprietary scientific datasets for model training and inference without requiring them to view or extract the underlying data," Robins said in the release.

How the deal compares

The A100 and Hopper are earlier Nvidia generations than the Blackwell and Vera Rubin systems CoreWeave has featured in other recent deals. CoreWeave's August agreement with Hudson River Trading specified access to Vera Rubin NVL72 and HGX B200 systems.

Without a disclosed contract value, investors cannot assess the agreement's contribution to CoreWeave's backlog. The announcement comes a week after CoreWeave launched a convertible notes offering and an at-the-market share program. CoreWeave completed a $4.2 billion convertible notes offering on September 22, including the full exercise of a $500 million purchaser option.

Frequently asked questions

What is CoreWeave's deal with Harell Data?

CoreWeave (CRWV) signed a multi-year agreement to run Harell Data's AI training, fine-tuning and inference workloads on its cloud, using Nvidia A100 and Hopper GPUs. The companies announced it on September 23, 2026, and did not disclose the contract's value, exact duration or computing capacity.

How does Harell Data keep proprietary data private?

Harell says it brings the model to the data. According to the company, training runs execute inside its platform and the raw datasets never leave it, so model builders never view or extract the underlying data. What the builder takes away is the trained model and the right to sell it.

How do data owners and model builders get paid on Harell's platform?

Harell meters compute per training run, and the dataset owner earns a revenue share on every job run against its data. Builders can list the models they train on Harell's marketplace and collect a fee each time someone runs them, an arrangement Harell calls Models as a Service.

More on CRWV and NVDA

Dennis Singleton
Dennis Singleton

Dennis Singleton has spent years following the markets, but what keeps his attention is how AI is built. He writes about the companies behind the technology, from semiconductor designers and advanced packaging to photonics, memory, networking, and the hardware powering modern AI. His approach starts with filings, earnings, and industry research, then translates the important details into clear, straightforward analysis without unnecessary hype.