Zenode.ai provides an AI-powered electronic component search engine that lets engineers find parts using natural language descriptions instead of exact part numbers. The platform searches across 25M+ components with answers grounded in datasheets and technical documentation, and offers API access for integration into engineering workflows.
Funding
Funding not disclosed
Founders
Product
Problem
Electronics engineers often face challenges locating components when they don't have exact part numbers or when they need to identify alternatives for obsolete or unavailable parts. Traditional search methods require precise manufacturer part numbers, which slows down design and procurement processes. Finding functionally equivalent replacements also requires manually comparing datasheets across suppliers, which is time-consuming and error-prone.
Solution
Zenode.ai provides an AI-driven component search engine that lets engineers describe what they need in plain language and get accurate part recommendations across millions of components. The platform searches over 25 million parts and returns answers grounded in real datasheets and technical documentation, ensuring reliability. Users can search by description, look up specific parts by manufacturer part number, find drop-in alternatives, and identify space-grade components. A Deep Dive feature extracts specifications from datasheets into tabular format for multiple parts at once, enabling efficient cross-part comparisons.
Target Audience
Electronics engineers, hardware designers, and procurement teams who need to identify components, find alternatives, or extract specifications efficiently across large part catalogs.
Features
- Natural language search across 25M+ components with AI-grounded answers from datasheets and technical specs
- Drop-in alternative identification based on electrical specs, package, availability, and manufacturer preferences
- Space-grade part detection with a 🚀 flag in search results
- Deep Dive feature that reads datasheets to fill in a table with requested data points across multiple parts
- REST API and Model Context Protocol (MCP) server for integration into external applications and engineering workflows