The startup offers an automation platform that utilizes 3D vision technology to enable real-time cloud-based recreation of physical environments using low-cost depth and 3D cameras. This platform simplifies the deployment of machine vision systems, making it easier for clients to implement large-scale video camera automation.
Funding
$13M 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
Existing machine vision systems often require complex and costly hardware setups for real-time 3D environment reconstruction. This complexity hinders the adoption of video camera automation, especially for large-scale deployments.
Solution
Aivero offers a platform that simplifies the deployment of machine vision systems by enabling real-time, cloud-based reconstruction of physical environments using low-cost 2D and 3D cameras. The platform provides an intuitive interface for streaming and capturing video data from multiple cameras, supporting both RGB and depth sensors. Aivero's solution facilitates efficient data compression, offering up to a 20:1 compression ratio for depth video, which reduces storage costs and accelerates data transfer. Users can choose between on-premise deployments for secure, offline machine learning or cloud-based solutions for scalable AI development. The platform is designed to optimize data generation, enabling the creation of large, proprietary datasets for AI research and development.
Target Audience
The primary target audience includes researchers in biomedical fields, particularly those focused on animal behavior, and developers of machine learning models who require efficient tools for capturing and managing visual data.
Features
- Real-time video streaming across multiple cameras, supporting 2D and 3D sensors
- Compatibility with a wide range of off-the-shelf cameras and hardware
- High-efficiency depth video compression (20:1 ratio) for storage savings and faster streaming
- On-premise and cloud-based deployment options for flexible machine learning development
- Browser-based tools for camera preview, management, and recording scheduling
- Support for 24/7 video capturing for continuous observation and data collection
- Hardware acceleration for efficient compression and low-bandwidth streaming