Predicting Wind Turbine Failures
Improved model results by
Reduced time to value by
Predicting Failures of 5G Radio Links
Augmented tower data with Weather data
Predicted failures 5 days in advance
Predicting likelihood of Loan Default
Improved model outcome by
Improved time to value from weeks to days
Identifying ideal Solar Farm sites
Automated a highly manual process
Reduced venture risk
Jumpstart your Machine Learning projects
Credit Risk Modeling
Predicting defaults during loan applications
Empowering data teams to deliver value rapidly
One Data Science Platform For Business and Technical Experts
For Expert Data Scientists For Citizen Data Scientists For Subject Matter Experts For Data Analysts For Data Engineers For Everyone
"Modeling in RapidCanvas was very easy. Out-of-the-box curated and validated solutions and templates within RapidCanvas made my development process error-free, reusable and repeatable and I didn’t get tripped up by third party library errors. After the entire machine learning lifecycle flow was implemented, the testing harness made it easy to analyze each code block. The interface also made it easy to identify the function of each code part, maintain and adapt it. Besides that, RapidCanvas helps generate insights and reports that I can share with business users and my clients."
"I have used RapidCanvas for a while now and can confidently say that it is among the best data science platforms for data practitioners. What I like in this tool other than its intuitive UI which gives a nice first impression of any given dataset is its division of code in different notebooks. The notebooks are divided such that the code’s readability and understandability remains intact."
"The main benefit of using RapidCanvas is that it spans the entire ML pipeline. The platform provides very sophisticated ML techniques and templates and a higher degree of performance and accuracy compared with other ML platforms I have used. Creating and training a models for any problem was easy and fast. It took me less than two weeks to master the platform and now I can easily handle large and complex data processing on the cloud. It really makes a difference in how I develop ML applications. The pipeline development paradigm makes implementing AI and ML use cases easier to drive business outcomes."
With multiple ready-made solutions with production-level quality, RapidCanvas makes it very easy to integrate AI in multiple industries. Moreover, their solutions can be easily customized to fit new realities, using a visual language that facilitates understanding from non-technical stakeholders. Their support team provides fast and accurate support to help you move your ideas to the platform.
RapidCanvas is a fast-growing platform for facilitating the implementation of machine learning solutions and outcomes that can be easily shared with a technical or non-technical client. It allows you to visualize the output of each step of your code and to create a better mental map of what your whole coding pipeline looks like, which is awesome and lets you spot any bugs in intermediate steps you might overlook with a 100% coding paradigm. The support and development team is very open, and quickly solves any tickets that come up.
We are on a mission to build a modern Multi-persona Data Science Machine Learning Platform that makes it easy for every data practitioner to combine their intuition and domain expertise with the power of automated machine learning.
Our mission is inspired by lessons from a multi-year journey of our founding team building machine learning platforms. The founding team's prior experience includes: being part of startups that went IPO, leading teams that built scaled platforms at PayPal and Google, and co-founding Simility, a startup backed by top-tier VCs with a successful exit.
We see a unique opportunity created by the intersection of interesting secular trends - enterprises transitioning to the cloud, post-covid acceleration of digital transformation, the continuing explosion of data, and realization in every organization that ML and AI need to be embraced in all areas of business.