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This Snowflake startup profile presents Dust as a multi-model platform for companies that want to use changing AI models without losing control of their data, workflows, or agent traces. The founder's claims about vendor lock-in and the value of traces are plausible but come from the company itself, and the piece offers no independent evidence of adoption or performance. For AI readers, the useful signal is the growing focus on owning the operational record of AI work, not just choosing a model.
Startup Spotlight: Dust’s Multi-Model AI Platform
Dust Co-Founder and CTO Stanislas Polu explains the vision behind Dust and how it helps companies own their AI by enabling control over agentic traces.
Welcome to Snowflake's Startup Spotlight, where we ask startup founders about the problems they're solving, the products they're building and the lessons they've learned during their startup journey. In this edition, meet Dust's Co-Founder and CTO, Stanislas Polu, and learn how the company is building a collaborative AI platform to reduce the distance between your data and the decisions your teams are making. What inspires you as a founder? I'm inspired by technical shifts that force us to question old assumptions. Large language models have made intelligence abundant, but abundance creates a new problem: How does a company use changing sources of intelligence without giving up control of what makes it unique? As AI spreads across individual tools and vendors, the company's context, agents and ways of working can become fragmented. I want to build the layer that lets organizations absorb constant progress while keeping those assets and…
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