Kern AI: Shaping the Future of Data-Centric Machine Learning
Kern AI provides the tools to improve data quality, from fixing label errors to enriching data by metadata
Kern AI provides the tools to improve data quality, from fixing label errors to enriching data by metadata
QDC.ai makes it easier to use optimization software involving a wide variety of optimization algorithms – even from quantum computing.
CELUS helps electronic engineers design new electronics by automating the schematics and PCB board design process using AI.
Envelope develops cutting-edge computer vision to extract essential information from images, videos, and camera streams
Tracebloc builds a platform where enterprises can showcase challenges and source machine learning models to solve these.
Alpha AR uses machine learning to automate the entire process of creating 3D models of real-world objects.
deepset provides tools to develop natural language interfaces quickly and efficiently and created the open-source framework Haystack.
Neurolabs uses synthetic images to update computer vision models within hours instead of weeks e.g for supermarket checkouts.
The Latvian startup Enot develops an AutoML framework for neural network compression and acceleration for the edge.
NannyML detects silent model failures that happen post-deployment – estimating model performance before historical data is available.