Deep Detection manufactures multispectral X-ray cameras that utilize direct photon counting and selectable energy bands to enable real-time inspection of production lines at speeds exceeding 60 m/min. Their technology identifies low-density materials and differentiates material types, ensuring the quality and safety of products in manufacturing and recycling processes.
Funding
$3M 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.
IIFounders
Product
Problem
Conventional X-ray inspection systems often miss low-density contaminants or fail to differentiate between similar materials, leading to inaccurate results and potential safety risks in manufacturing and recycling processes. These limitations can result in increased false positives, costly product waste, and undetected hazards.
Solution
Deep Detection provides multispectral X-ray cameras that utilize direct photon counting and selectable energy bands to enable real-time inspection of production lines. Their technology enhances detection capabilities with multi-energy imaging and AI-driven analysis, improving efficiency while reducing false positives. The cameras differentiate material types, physical parameters, chemical signatures, and composition, even at production line speeds exceeding 60 m/min. Deep Detection's spectral X-ray cameras improve the detection of hazards and minimize the risk of undetected contaminants.
Target Audience
Deep Detection's primary customers are manufacturers and recycling facilities seeking advanced inspection technology to ensure product quality, safety, and compliance with evolving regulatory standards.
Features
- Direct photon counting for precise, real-time data resolution and sharp images.
- Selectable energy bands providing multi-layer color images for enhanced material differentiation.
- Continuous inspection at production line speeds of 60 m/min and higher.
- Detection of low-density materials, including plastics and lightweight glass, even in inhomogeneous mixes.
- Material characterization to differentiate material types, physical parameters, chemical signatures, and composition.
- AI-powered material separation to reduce false positives and product waste.
- Low-noise sensors for unmatched sensitivity in revealing contaminants.
- Pixel precise dual energy imaging using two imaging channels per pixel to distinguish contaminants by their X-ray energy signature.