Activeloop.ai raised $11 million in Series A funding round. Activeloop’s innovative technology, Deep Lake, promises to transform how enterprises leverage multimodal data for AI applications.
The Challenge: Enterprises face a significant hurdle when it comes to handling unstructured multimodal data (such as images, videos, and annotations) for training AI models. Traditional storage solutions fall short in terms of cost-effectiveness and efficiency.
The Solution: Deep Lake:
Activeloop’s Deep Lake stores complex data in the form of machine learning-native mathematical representations (tensors). It enables seamless streaming of these tensors to SQL-like Tensor Query Language, visualization engines, and popular deep learning frameworks like PyTorch and TensorFlow. By doing so, Deep Lake reduces costs by up to 75% compared to existing market offerings while increasing engineering teams’ productivity by up to five-fold.
The Impact:
Enterprises can now tap into their diverse and complex datasets with ease, accelerating AI development across various use cases. Activeloop’s mission is to democratize AI data management, benefiting Fortune 500 companies and beyond.
