
Pluralis Research enables organizations and communities to collaboratively train and own large foundation models using a decentralized protocol. It provides a protocol-level framework for decentralized training, contribution tracking, and shared ownership of model weights and checkpoints. The company focuses on open-source foundation models and collaborative workflows, combining peer-to-peer coordination with cryptographic provenance for contributions. Pluralis Research is an AI protocol startup targeting teams and institutions that need governed, decentralized model training and ownership.

Pluralis Research enables organizations and communities to collaboratively train and own large foundation models using a decentralized protocol. It provides a protocol-level framework for decentralized training, contribution tracking, and shared ownership of model weights and checkpoints. The company focuses on open-source foundation models and collaborative workflows, combining peer-to-peer coordination with cryptographic provenance for contributions. Pluralis Research is an AI protocol startup targeting teams and institutions that need governed, decentralized model training and ownership.
Core focus: Decentralized, multi‑participant training of foundation models (Protocol Learning)
Founded: 2024
Headcount (approx.): 16
Notable investors: CoinFund, Union Square Ventures, Amazon Web Services, Balaji Srinivasan
Total funding reported: USD 8,600,000
| Company |
|---|
Decentralized/federated training of large language models and governance of shared model ownership.
2024
Data and Analytics
Seed announced March 19, 2025; some sources report lead investors as CoinFund and Union Square Ventures
“Includes institutional crypto/VC and notable individual investors (e.g., CoinFund, Union Square Ventures, Amazon Web Services, Balaji Srinivasan, Clem Delangue, Variant, Eden Block, Bodhi Ventures, topology)”
Pluralis Research is pioneering Protocol Learning—a fully decentralised way to train and deploy AI models that opens this layer to individuals rather than well resourced corporates. By pooling compute from many participants, incentivising their efforts, and preventing any single party from controlling a model’s full weights, we’re creating a genuinely open, collaborative path to frontier-scale AI. If you want your work to shape the future of truly open innovation in artificial intelligence, join us.
Key Responsibilities
What We're Looking For