The startup offers a digital inventory platform that utilizes machine learning to optimize supply chain operations by integrating technical data with on-demand manufacturing processes. This platform enables industries to accurately identify necessary parts, reducing the need for excessive hardware investments and enhancing collaboration with software and logistics partners.
Funding
$2.7M 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
Many companies struggle with inefficient supply chains due to inaccurate inventory management, high hardware costs, and limited collaboration with manufacturing and logistics partners. Identifying the right parts for on-demand manufacturing and optimizing designs for additive manufacturing can be challenging and time-consuming.
Solution
Dimanex offers a digital inventory platform that leverages machine learning to optimize supply chain operations through additive manufacturing. The platform analyzes supply chain and technical data to identify suitable parts for on-demand manufacturing, enabling businesses to reduce hardware and tooling investments. It facilitates the digitization of parts, allowing for secure digital inventory management and streamlined order placement with global manufacturing facilities. Dimanex also provides tools to optimize part designs for additive manufacturing, further reducing costs and improving efficiency.
Target Audience
The primary target audience includes small to medium-sized enterprises (SMEs) and large businesses seeking to optimize their supply chains, reduce costs, and improve sustainability through additive manufacturing, as well as software partners looking to enhance their offerings with additive manufacturing analytics.
Features
- AI-based analytics to identify supply chain optimizations and evaluate parts for additive manufacturing
- Secure digital inventory for uploading and managing part designs
- Workflow tools for order management and delivery
- Global sourcing of parts from a network of manufacturing facilities
- Identification of parts with potential for redesign to reduce costs in additive manufacturing
- CO2e Reduction Indicator to identify opportunities for reducing carbon emissions
- API integration for software partners to embed additive manufacturing analytics