AI applications can seem like a complex and convoluted world. Fortunately, that’s about to change.
Kogentix Automated Machine Learning Platform ( AMP) makes it possible to build, manage, monitor, and deploy enterprise grade AI applications all on an effective, scalable open source software. With AMP you don’t have to waste time scripting and managing a wide variety of ever changing tools.
Business leaders, data scientists , analysts and engineers can focus on using their data to enable impacting business actions. For data to have an impact, the entire machine learning application process must be automated, operationalized and governed.Kogentix AMP delivers.
The AMP Advantage
Innovate. Automate. Operate.
Innovation requires market leadership, and leadership is gained through velocity. AMP offers the capability to rapidly integrate data, discover trends, and iterate on models to drive the best business outcome.
- Kogentix AMP connects to a broad variety of data sources, enterprise or external, streaming or batch. Richer and more diverse data yields the potential for patterns and correlations that would otherwise remain hidden.
- Kogentix AMP enable insights, recommendation to be integrated with business systems as APIs or real time. AMP also includes a rules engine that can generate triggers based on a set of domain specific conditions, making it even easier to create a business impact from a simple user interface.
- AMP provides capability to users to integrate user defined rules with machine learning. This results in building applications which enable human knowledge intervention and action.
As the demand for AI solutions increases, enterprises will look to expand their data science capacity in 2 main ways. Firstly by enabling experienced data scientists to be more productive, and secondly, by enabling business users to leverage machine learning. Kogentix AMP creates additional capacity through automation, a business focused interface, and elimination of coding and scripting.
- AMP delivers automated capability throughout the application life cycle. Users can immediately see correlations as causal analysis soon as the data loads. AMP can even automatically recalibrate a model once it’s in production. Of course, all of these automations are transparent and can be overwritten and controlled by the user.
- Data wrangling, a time consuming but necessary task, is made much simpler using AMP. With a simple drag and drop interface, users can join datasets, filter data, deal with missing values that could skew results, and identify key data elements that are more important.
- Once a workflow has been created, AMP automates the production deployment. The user simply selects deploy, enters some parameters, and deploys with a single click.
Over time, machine learning models lose accuracy as input data changes – maybe a competitor introduces a new product or service; a news event triggers a change in customer attitudes; usage patterns change on an IoT device. AI applications need to have enterprise security, governance, and reliability, but they also need to adapt. Kogentix AMP eliminates the tradeoff between production robustness and adaptability.
- AMP runs natively on a distributed big data platform, taking advantage of fine grain security and access control, governance, and resiliency. All of the data leveraged by AMP remains in the underlying data platform, avoiding challenges with data consistency.
- AMP is built for versatility of deployment. It can be installed in a customer’s data center, on a customer’s own cloud instance, or deployed as a cloud service. Customers keep control of their data, and their insights.