Dust Raises $40M to Push Enterprise AI Beyond Single-Player Era
The Paris- and San Francisco-based platform’s Series B is co-led by Abstract and Sequoia, with Snowflake and Datadog participating. Total funding now exceeds $60 million.
Dust, a Paris- and San Francisco-based enterprise AI platform, has secured a $40 million Series B led by Abstract and Sequoia, with the participation of Snowflake and Datadog. This round brings Dust’s total funding to over $60 million, building upon its previous $16 million Series A in June 2024, also led by Sequoia.
Dust proposes a unique argument about the shortcomings of current enterprise AI: the dominant model has been individual assistants, with each session’s context disappearing into private chat windows once completed. They refer to this as ‘single-player AI’ and their own product as the ‘multiplayer’ alternative—a shared workspace where agents and employees can access projects, conversations, files, notifications, and to-do lists from a central hub, connected to existing company systems.
As stated by Gabriel Hubert, Dust’s co-founder and CEO: "What will transform the way we work isn’t the next best model or assistant. It’s going to be a completely new type of system that gives humans and agents shared, governed access to the same information and capabilities so they become true collaborators."
The company positions itself as a competitor to single-user copilots from foundation-model labs and software incumbents. With over 3,000 organizations using Dust, 41,000 monthly active users in April, and more than 300,000 agents deployed, the platform boasts a strong user base. They claim a 70% weekly active usage across their customer base and zero customer churn in 2025.
Dust’s capabilities include:
- Integration with over 100 data sources
- Memory layers and agent analytics
- SOC 2 Type II certification and GDPR compliance with EU and US data residency
- Contractual commitments from providers not to train on customer data
Customer testimonials highlight significant time savings. At Vanta, the CRO estimates a reduction of 400+ hours per week, while Watershed achieved an 85% success rate in reducing a recurring data-mapping workflow from three hours to just minutes.
The enterprise AI space is becoming increasingly competitive with companies like Anthropic, Google, Microsoft, and OpenAI introducing their own agentic tools.