What is better Receptiviti or Azure Machine Learning Studio? It’s easy to our scoring system to give you a general idea which AI Software product is more suitable for your company. For overall product quality, Receptiviti received 6.5 points, while Azure Machine Learning Studio gained 9.5 points. Meanwhile, for user satisfaction, Receptiviti scored 100%, while Azure Machine Learning Studio scored 97%.
Specifics of their characteristics, tools, supported platforms, customer service, plus more are provided below to provide you with a more versatile analysis. Remember to purchase only the tools your company needs so as not to waste resources for features which are redundant.
If you need to quickly decide on the best AI Software according to our experts we recommend you check out the following products: Salesforce Einstein, Azure Machine Learning Studio, Google Vertex AI.
Receptiviti is an innovative AI-powered platform that combines techniques from different sciences. Enterprises who wish to utilize the platform can request for their enterprise pricing and ask for more information through email or web form.
Azure Machine Learning Studio offers the following enterprise pricing packages for users to choose from. Give the details a look, and select the best plan for your business.
Azure Machine Learning Studio offers APIs for developers’ use. For more information, contact support or get in touch with the community.
Languages Supported
English
Chinese
German
Hindi
Japanese
Spanish
French
Russian
Italian
Dutch
Portugese
Polish
Turkish
Swedish
Arabic
Prominent Clients
Mendeley, Rockwell Automation, Stanford’s SLAC National Accelerator Laboratory
Available Devices
Windows
Linux
Android
iPhone/iPad
Mac
Web-based
Windows Mobile
Company Size
Small Business
Large Enterprises
Medium Business
Freelancers
Available Support
email
phone
live support
training
tickets
General Info
A cloud-based interactive programming tool for predictive analytics from Microsoft. Azure Machine Learning Studio offers access to Cortana Intelligence Suite and gallery, AI algorithm library, and more. Its easy to use interface utilizes drag and drop actions. Despite being cloud-based, this machine learning solution provides offline access to its users.
If you continue having second thoughts about which software will be best for your company it may be a sensible idea to take a look at each service’s social metrics. Such metrics are quite often a sign of how popular each app is and how extensive is its online presence. For example, in case of Facebook Receptiviti has 65 likes on their official page while Azure Machine Learning Studio profile is liked by 500122 people.
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