Competitive Analysis: Stratifyd's All-in-One Competitors


With a foundation in data science, Stratifyd has created one of the most versatile AI powered data analytics tools on the market. We believe that our platform, leveraging machine learning and natural language understanding, is among the top solutions for data analysis available. With that in mind, Stratifyd is punching above our weight by stepping into the ring with some of the biggest names in enterprise technology. In order to determine how we stack up against them, we analyzed the different services they provide and compared them to our capabilities.

The companies on this list need no introduction. They are among the most prominent companies in the business for technology solutions. Their products service some of the most well known companies in business to provide data analysis on a broad category of information. We at Stratifyd understand the offerings that the companies on this list provide and have tailored our product to match their capabilities across the board. In order to understand how we compare, its necessary to understand what each service entails. Below is a breakdown of each solution that provides deeper knowledge into its function.


Collaboration - The ability to share insights with other team members is crucial to creating faster time to action. Collaborative processes are those that allow easy sharing of reports or dashboards within the team or to other relevant decision makers.

Text Analytics - Most data is in the form to text whether it be structured or unstructured. Text analytics refers to analyzing information from text data and understanding the significance within a textual data set.

Machine Learning - Artificial intelligence is pushing new boundaries across data analytics. Machine learning refers to using that artificial intelligence to automatically process and analyze data to determine significant relevance.

Visualization - Data analysis is only as good as how well you can understand it. Visualization allows for easy assessment of the data through charts, graphs, word clouds, and other visual medium within what the industry refers to as a dashboard.

Sentiment Analysis - When analyzing text data, it is important to understand the meaning behind the words. Sentiment analysis gives businesses the opportunity to understand the feeling and intent behind the words and use that knowledge for action.

Data Preparation - Creating a suitable data format to begin analysis can be a laborious process, and can require powerful tools. Data preparation provides the ability to manage and manipulate information within the same analysis platform saves the headache of integrating different tools.

Statistical Computing - Visualizing your data is important on the surface, but doesn't always help you understand the next level deeper: what is significant and what is not. Statistical computing helps analyze hidden patterns and trends that aren't always apparent to the naked eye.