Activeloop frees deep learning teams from building complex data infrastructure so they can develop AI products faster. It simplifies the deployment of enterprise-grade LLM-based products by offering storage for all data types (embeddings, audio, text, videos, images, pdfs, annotations, etc.), querying and vector search, data streaming while training models at scale, data versioning and lineage for all workloads, and integrations with popular tools such as LangChain, LlamaIndex, Weights & Biases, and many more.
"Activeloop's Deep Lake helped us focus on building the product instead of worrying about scalable data infrastructure. It enabled us to efficiently host multiple collections in memory, overcoming the synchronization …
“As the datasets enlarge and become multi-modal, next-gen solutions built specifically to address those use cases, like Deep Lake, will help AI teams deliver models to production faster, and more …
“A 100x speedup of Tensor Query execution for semantic search and question answering on legal documents. Deep Lake’s minimalistic architecture provided flexibility and light touch installation for our customers without …
Read Activeloop Reviews, Testimonials & Customer References from 11 real Activeloop customers.
Browse Activeloop Case Studies, Customer Success Stories, & Customer References from 6 businesses that use Activeloop.
FeaturedCustomers has 1,899,696+ validated customer references
including reviews, case studies, success stories, customer stories,
testimonials and customer videos that will help you make better
software purchasing decisions.
