Exa AI vs Skild AI
Side-by-side comparison of AI visibility scores, market position, and capabilities
AI-native search API raised $85M Series B at $700M valuation in Sep 2025 backed by Nvidia and Benchmark; revenue hit $10M with 1,010% YoY growth; powers semantic web retrieval for LLM and RAG pipeline applications.
About
Exa AI is an AI-native search and retrieval company building a fundamentally different kind of web search infrastructure designed specifically for AI systems and developers. Founded on the premise that keyword-based search engines are poorly suited to serve as data sources for large language models, Exa developed a neural search architecture that retrieves web content based on semantic meaning rather than keyword matching — enabling AI applications to find relevant, high-quality information the way reasoning systems think about queries.\n\nExa's API allows developers to perform meaning-based web searches, retrieve full page contents, find similar documents, and access curated data streams for AI training and retrieval-augmented generation pipelines. It is designed as AI infrastructure: the underlying retrieval layer that powers AI agents, research tools, and automated workflows that need accurate, current web information. Target customers are AI developers, research teams, and enterprises building AI-powered products that require reliable web grounding.\n\nExa AI raised $85M in a Series B at a $700M valuation in September 2025, backed by Nvidia and Benchmark Capital. The company's revenue hit $10M with 1,010% year-over-year growth — one of the fastest growth rates in the AI infrastructure category. Nvidia's strategic investment reflects Exa's importance as a retrieval layer in the broader AI stack. As AI agents proliferate and need reliable access to real-time web knowledge, Exa's semantic search API is positioned as essential infrastructure for the next generation of AI applications.
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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