Also known as: numericcal, Numericcal
Distributed AI for Industrial Process Monitoring and Optimization.
Company is closed
Event Year: 2018
Company is closed
Event Year: 2018
Numericcal, Inc. provided comprehensive solutions for anomaly detection, asset tracking, and workforce management specifically tailored for the automotive and manufacturing sectors. Their approach involved leveraging advanced machine learning techniques to analyze unstructured sensory data, including video and audio feeds. By deploying their solutions across both edge computing environments (on-premises) and multiple cloud platforms (Azure, AWS, and GCP), Numericcal aimed to significantly reduce operational costs—reportedly by a factor of 100—while simultaneously enabling the processing of substantially larger datasets, exceeding the capabilities of purely cloud-based alternatives. This distributed architecture was also intended to enhance reliability and safety within industrial operations.
Numericcal, Inc. provided comprehensive solutions for anomaly detection, asset tracking, and workforce management specifically tailored for the automotive and manufacturing sectors. Their approach involved leveraging advanced machine learning techniques to analyze unstructured sensory data, including video and audio feeds. By deploying their solutions across both edge computing environments (on-premises) and multiple cloud platforms (Azure, AWS, and GCP), Numericcal aimed to significantly reduce operational costs—reportedly by a factor of 100—while simultaneously enabling the processing of substantially larger datasets, exceeding the capabilities of purely cloud-based alternatives. This distributed architecture was also intended to enhance reliability and safety within industrial operations.
Total Raised: Unknown (Y Combinator backed)
Last Round: Summer 2018
Total Raised: Unknown (Y Combinator backed)
Last Round: Summer 2018
B2B
B2B
B2B -> Engineering, Product and Design
B2B -> Engineering, Product and Design
Team size: 3
Hiring: No
Team size: 3
Hiring: No