ChipAgents vs Skild AI
Side-by-side comparison of AI visibility scores, market position, and capabilities
Agentic AI for chip design. 140x YoY ARR growth. 80 semiconductor customers. $74M raised ($50M Series A1 led by TSMC-backed fund). Founded 2024, Santa Clara.
About
ChipAgents was founded in 2024 in Santa Clara, California, to apply agentic AI to one of technology's most complex and bottlenecked workflows: semiconductor chip design. The company's founding insight is that chip design — a process that requires months of highly specialized engineering work across logic synthesis, physical layout, verification, and timing closure — is an ideal domain for AI agents that can autonomously navigate design rule constraints, run simulations, and iterate on solutions faster than human engineers.\n\nChipAgents' platform deploys multi-agent AI systems that operate across the electronic design automation (EDA) toolchain, automating tasks in RTL design, floorplanning, placement and routing, and design verification. Rather than augmenting individual EDA tools with AI features, ChipAgents takes an end-to-end agentic approach in which AI agents coordinate across the full design flow, flagging issues, proposing fixes, and running iterative optimization loops with minimal human intervention. This positions the platform as a force multiplier for semiconductor engineering teams facing growing design complexity and talent shortages.\n\nChipAgents achieved 140x year-over-year ARR growth and has secured 80 semiconductor customers, demonstrating rapid enterprise adoption in a traditionally conservative industry. The company raised $74M, including a $50M Series A1 led by a TSMC-backed investment fund — a strategic signal of validation from the world's largest chip manufacturer. Founded just one year before its Series A, ChipAgents represents one of the fastest-growing AI infrastructure companies in the semiconductor ecosystem.
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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