Dust vs Skild AI
Side-by-side comparison of AI visibility scores, market position, and capabilities
Paris-based AI assistant platform for teams; raised $21.5M total (Sequoia-led); hit $7.3M ARR with 66-person team; connects company data to LLMs securely
About
Dust is a Paris-based enterprise AI assistant platform founded to help teams connect their internal knowledge and data to large language models in a secure, governed way. The company was founded by former Stripe engineers who saw that the core challenge in deploying AI at work was not the model itself but the data integration layer — making company knowledge accessible to AI without creating security and compliance risks. Dust's platform allows organizations to connect data sources like Notion, Slack, GitHub, Google Drive, and custom internal tools into a unified knowledge layer that powers AI assistants tuned for the company's specific context.\n\nDust's product enables teams to build and deploy custom AI agents — internally called "assistants" — that can answer questions, summarize documents, draft communications, and complete workflows using the company's proprietary data. The platform includes role-based access controls, ensuring that AI assistants only surface information appropriate for the requesting user's permissions. Customers use Dust to replace fragmented AI experiments across different departments with a centralized, IT-governed deployment that scales across the organization.\n\nDust raised $21.5M in total funding, including a Sequoia-led round, and reached $7.3M ARR with a 66-person team — a capital-efficient growth profile that reflects the founders' engineering discipline. The company competes in the enterprise AI assistant market against Microsoft Copilot, Glean, and Notion AI, differentiating through its developer-friendly customization, European data residency options, and focus on mid-market companies that need enterprise-grade governance without the complexity of large-company deployments.
Universal robot brain startup raised $1.4B Series C at $14B valuation in Jan 2026 led by SoftBank with Nvidia and Bezos; $30M 2025 revenue; deployed at Foxconn
About
Skild AI is building a universal robot brain — a foundation model for physical intelligence that can power a broad range of robot types without requiring task-specific training for each deployment. Founded to solve the fragmentation problem in robotics AI, where every robot type and task requires separate model development, Skild's approach trains a single generalist model on diverse robotic data and fine-tunes it rapidly for specific deployments. The company was founded by robotics AI researchers who identified the model reuse gap as the primary barrier to scalable robot deployment.\n\nSkild's generalist robot model has been deployed across more than 30 distinct robot types — spanning manipulation arms, mobile platforms, and humanoid form factors — demonstrating the cross-hardware generalization that most robot AI systems lack. The platform targets robotics manufacturers, logistics operators, and industrial automation companies that need AI-capable robots but lack the internal ML infrastructure to develop foundation models themselves. By offering a model-as-a-service layer, Skild enables robot OEMs and systems integrators to add AI capabilities without building the underlying research infrastructure.\n\nSkild AI raised a $1.4 billion Series C in January 2026 at a $14 billion valuation, led by SoftBank with co-investment from NVIDIA and Jeff Bezos. The round was one of the largest in robotics AI history and reflects institutional conviction in the physical AI market's scale. With $30 million in 2025 revenue and accelerating enterprise deployments, Skild is building the financial foundation to match its valuation. The SoftBank-NVIDIA investor combination positions Skild at the center of the global robotics deployment wave.
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