PartGenie is an AI hardware companion for electronics design and component sourcing. It helps hardware engineers, R&D teams, and procurement professionals quickly find the right electronic components and make more informed sourcing and design decisions.
Search across 22M+ electronic components from 7,700+ manufacturers using part numbers or natural-language requirements. PartGenie provides datasheet-backed specifications, ranked alternatives, BOM risk analysis, and sourcing context.
PartGenie also helps engineers analyze datasheets, identify obsolete or risky parts, discover replacement options, and streamline hardware development workflows.
PartGenie’s BOM Analyzer specifically supports EOL detection, missing-spec checks, supply-chain risk identification, and replacement suggestions.
Datasheet AI can extract specifications and answer technical questions, while PartGenie’s component pages provide ranked alternatives and datasheet-backed information.

We built PartGenie because hardware engineers and procurement teams still spend too much time searching for components, reading long datasheets, comparing alternatives, and checking BOM risks manually. PartGenie brings these workflows together with AI — helping teams search components using natural language, analyze datasheets, identify suitable alternatives, and review BOM lifecycle and sourcing risks in one place. Our goal is simple: make hardware component research and sourcing faster, more reliable, and easier for engineering teams.

We built PartGenie because hardware engineers and procurement teams still spend too much time searching for components, reading long datasheets, comparing alternatives, and checking BOM risks manually. PartGenie brings these workflows together with AI — helping teams search components using natural language, analyze datasheets, identify suitable alternatives, and review BOM lifecycle and sourcing risks in one place. Our goal is simple: make hardware component research and sourcing faster, more reliable, and easier for engineering teams.
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