ZENODE| Machine to Machine Learning
Finding the right electronic components is one of the most time-intensive and critical steps in hardware development. Engineers must sift through millions of parts, each with datasheets structured differently—packed with technical specifications, graphs, equations, and footnotes. A single mistake in component selection can lead to costly redesigns, manufacturing delays, or even product failures. Zenode solves this problem by providing an AI-driven search engine that enables engineers to instantly query millions of electronic components using natural language.
Unlike traditional part search tools, Zenode allows users to refine their search dynamically using parametric filters and additional context to improve AI rankings, ensuring that engineers get the most relevant results. Instead of manually searching through datasheets, users can interact directly with them—asking AI-powered queries and receiving highlighted responses with citations from the datasheet itself. This removes friction from the component selection process, enabling teams to move faster with confidence.
Zenode is more than just a search tool—it’s the first step toward AI-powered electronic design automation (EDA). By building a deep understanding of electronic components and how engineers interact with them, Zenode is positioned to expand into schematic generation, board layout, and procurement automation. Starting with search—the gateway to every hardware project—Zenode is transforming how engineers design, source, and integrate components at scale.
COMPANY PROFILE:ZENODE
Revolutionizing Electronic Component Search with AI.
Zenode is the first step toward AI-driven electronic design automation (EDA). By perfecting search and selection, Zenode builds a deep understanding of components—laying the foundation for future AI-powered schematic generation, board layout, and procurement.
FOUNDERS:
→ Brandon Bourn
→ Collin Stoner
LAST FUNDING STAGE:
Pre-Seed
VECTOR:
Machine to Machine Learning
3
Team Members
600K
Funding to Date
FOUNDER
CO-FOUNDER
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