Is your business ready for AI?

With more businesses wanting to implement AI driven automation to improve operational efficiency and provide greater customer satisfaction, it is important to understand if the current data infrastructure is good enough to address these goals.

Increasing interest in AI has encouraged data engineers to come out with solutions which will help in automating processes such as machine driven customer engagement, operational workflows, Predictions and Solution Paths (Prescriptions), or even addressing unit economics.  By automating business processes, we are not too far behind in providing a highly supervised environment to monitor and manage these machines.

However, to expect such a machine that can generate AI driven business decisions, a business has to carefully plan their data environment and make sure if the following factors are addressedTo solve the above challenges, it is evident that the business needs a unified data platform. Today, enterprise data environments are littered with data silos, and unifying this data is the biggest challenge which needs to be addressed first, as it forms the data foundation for every new innovation or learning that the business would want to experiment.

 

About Plumb5
Plumb5 is a unified data platform that is designed keeping all the above conditions in mind. Plumb5 to its current capabilities can automate 65-70% of business processes paving the way for machine driven business operations.

Using the data connectors, data can be plugged into the learning network for real-time learning and intelligence. The weights defined by the learning network allowing the system to compute output states as soon as the input data is ingested into the network. The data “states” act as the markers for the automation engine to trigger relevant next actions.

If you would like to know more or would like to test it out on your data, you can contact the data team@plumb5 .

2 Comments

    1. Classification is done by mapping input data to a preset structure of categories. When data sources are integrated for creating a unified master, the classifier will tag data automatically to a given category, based on rules. The manual part(supervised part) is to map the column names to the editable category list within the classifier. The category list is derived from the subject areas defined in the information architecture. Please refer to the link below to check more on the classification hierarchy within the data model
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