
AI & Machine Learning Operationalization (MLOps) Software
Massive amounts of data being created at the edge, uploading this data to the cloud for real-time analysis is neither financially nor technically feasible. Extracting meaning from this data is computationally intensive and expensive, limiting adoption of edge AI to a few high-value applications. After years...
- Revenue
- $1.5M
- Customers
- -
- Year founded
- 2017
- Funding
- $123.6M
- Team size
- 14
- Location
- United States














