Partium offers an AI-based parts search platform that utilizes visual search, text recognition, and data enrichment techniques to enable technicians and supply chain staff to locate spare parts quickly and accurately. By optimizing existing parts data and reducing search times by up to three times, Partium enhances the efficiency of aftersales operations and improves customer satisfaction.
Funding
$28.7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Technicians and supply chain staff often struggle to quickly and accurately locate spare parts due to inefficient search methods and incomplete parts data. This leads to prolonged downtime, increased operational costs, and reduced customer satisfaction in aftersales operations.
Solution
Partium offers an AI-powered parts search platform that streamlines the identification and procurement of spare parts. By leveraging visual search, text recognition, and data enrichment techniques, Partium enables users to quickly find the parts they need. The platform optimizes existing parts data by adding critical information, deduplicating entries, and facilitating lifecycle management. Partium's AI-driven approach reduces search times, improves the accuracy of part identification, and enhances the overall efficiency of aftersales processes.
Target Audience
Partium is designed for technicians, supply chain professionals, and maintenance teams in industries such as rail, manufacturing, and energy, who require a fast and reliable solution for spare parts identification.
Features
- Visual search using images, code detection, and optical character recognition (OCR)
- Semantic and exact text search capabilities
- Attribute filters based on bill of materials (BoM)
- Data insights for identifying missing or duplicate master data
- Identification of parts with missing manufacturer IDs
- External data enrichment from various sources
- Internal data enrichment using technical documentation and CAD files
- Collaborative enrichment through part search activity and image capture