The startup develops hardware-agnostic solutions for visual-input-based process automation, utilizing geometry and texture-based attributes to enhance task execution. Their technology targets the inefficiencies of labor-intensive, repetitive tasks, providing businesses with consistent output and increased operational flexibility.
Funding
$200K 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 manufacturing, intralogistics, and healthcare companies still rely on manual labor for repetitive tasks such as bin picking, palletizing, and quality inspection, leading to inefficiencies and potential errors. Automating these processes can be complex and costly, often requiring specialized vision expertise and extensive programming.
Solution
BitMetrics offers AI-powered, hardware-agnostic computer vision and vision-guided robotics solutions designed to automate repetitive manual processes. Their solutions, including Pick+, Pick+ Palletizer, and Scan+, enable robots and machines to identify, select, and manipulate items, as well as perform visual inspections with minimal human intervention. The technology leverages geometric and texture-based attributes to ensure consistent output and increased operational flexibility. BitMetrics' software is designed to be user-friendly, allowing non-vision experts to easily design and maintain their automation processes.
Target Audience
BitMetrics targets companies in manufacturing, intralogistics, and healthcare seeking to automate repetitive manual tasks, including those involved in bin picking, palletizing, and visual inspection.
Features
- Pick+: Enables robots to identify items, select pick candidates, avoid collisions, and place items in the required pose and location.
- Pick+ Palletizer: Automates palletizing and depalletizing tasks, generating optimal pallet patterns and handling both 2D and 3D contexts.
- Scan+: Automates vision-based processes such as item counting, presence/absence detection, classification, defect detection, and pattern deviation analysis.
- Hardware-agnostic design allows integration with existing cameras and robots.
- AI-powered technology enables grasping of known and unknown objects, including flexible, malleable, and shiny shapes.
- User-friendly interface with guided calibration and application creation, requiring no coding.
- Pre-trained models and one-shot/few-shot training options for specific use cases.