Dust

Global – October 27, 2026 -- Dust, a collaborative AI platform, is targeting three forms of enterprise AI dependency: reliance on a single model provider, loss of control over agent-generated data, and limited visibility into costs and behavior, according to Co-Founder and CTO Stanislas Polu.

Dust builds a shared layer between staff, company data and multiple models

Polu said Dust lets teams work with AI, switch among supported frontier and open source models, and govern the context, agents and traces their work generates. The platform is multimodel by design, so companies can change models without rebuilding their context and workflows.

Polu argues that agent traces, which record instructions, context, model and tool choices, outputs and human feedback, may become one of a company's most valuable AI assets. He said that corpus could later help companies evaluate or train models for their specific work.