Ople Competitors, Revenue, Alternatives and Pricing
Estimated Revenue & Financials
- Ople's estimated annual revenue is currently $7.5M per year.
- Ople received $8.0M in venture funding in October 2018.
- Ople's estimated revenue per employee is $145,000
- Ople's total funding is $8M.
- Ople has 52 Employees.
- Ople grew their employee count by 18% last year.
- Ople currently has 3 job openings.
What Is Ople?
Today, business leaders are frustrated with the lack of delivery from artificial intelligence. Results take too long, the risks are too high, and it's challenging to find competent professionals with the right skill sets and experience. We are building the platform that addresses these issues. At Ople, we use AI to build AI. We have developed an AI platform that acts, thinks, and learns like a data scientist. Our software optimizes the entire Data Science processes, going from data to predictions in days instead of months. Ople delivers elite quality deep learning models deployed instantly and ready to make predictions. With Ople's speed and the confidence it inspires, business leaders are no longer content with two to three projects per year. Data scientists are free to unleash the creativity and imagination to truly impact the business while Ople's platform takes care of the execution. Our goal is to fundamentally change data science and disrupt all industries by making artificial intelligence Easy, Cheap and Ubiquitous. Our founder Pedro Alves asked a question, How can I become a better data scientist Quickly realizing that he was learning by observing how algorithms learn from processing different models, Pedro recognized that many data scientists would benefit from AI that mimics this behavior of learning to learn to learn. Hence, Ople was born. We are a diverse team of world-class data scientists, machine learning experts, engineers and market makers. We strive to change data science and revolutionize businesses across industries. To fulfill our vision, > We listen and collaborate: Everything is open for discussion, and we work as one team. > We seek the right answer, not to be right: We make mistakes and keep learning. > We expect to lead: We speak up and are respectful. We are curious individuals who relentlessly challenge ourselves. We are never satisfied. If you are this passionate about data science and enjoy learning, join us!keywords:Machine Learning, Big Data, Artificial Intelligence