Shaip has been a recognized industry leader in the fields of conversational and medical AI with its ability to source, curate, and transcribe data in more than 50 languages from across the globe.
Fremont, CA: Shaip, a global leader and innovator in AI data solutions, has declared the launch of its industry-agnostic AI training-data platform ShaipCloud. ShaipCloud was developed to transform unstructured text, speech, image, and video data into customized, high-quality datasets utilized to train artificial intelligence as well as machine learning algorithms. This new platform rounds out Shaip's already resilient service offering that includes data licensing, collection, transcription, data labeling/annotation, and data de-identification to help clients solve their most demanding AI initiatives, enabling faster, smarter, and better results.
A natural extension to ShaipCloud is Shaip Recording App, available on both Google and Apple app stores. Skilled workforces across the globe can join Shaip's team as an independent contributor for data labeling& annotation.
Sourcing high-quality training data has always been a primary bottleneck to make AI work in the real world. Shaip concentrates on delivering end-to-end AI training data solutions that generate intelligence and value at scale for its clients. This is all made possible through a unique combination of its proven processes, human-in-the-loop platform, and skilled global workforce. With all the elements in place, Shaip can license, create, or transform unstructured data into highly accurate as well as customized training datasets to meet even the most stringent timeline and budgets.
Shaip has been a recognized industry leader in the fields of conversational and medical AI with its ability to source, curate, and transcribe data in more than 50 languages from across the globe. Additionally, Shaip's highly curated and de-identified healthcare datasets contain millions of patient records and also thousands of hours of patient audio spanning 31 medical specialties and COVID-19 data.