Pegasystems announced on Tuesday that it is adding the ability to apply AI to business processes midstream, intending to help organizations determine whether an anticipated outcome will turn out as predicted.
Pegasystems is introducing another feature that companies can use to analyze streaming event data on platforms like open-source Apache Kafka software, which many organizations use to transfer data, almost in real-time.
Pega Process AI brings together machine learning algorithms, natural language processing, business rules, event processing, and predictive analysis, with low-code tools for analysis in real-time.
Organizations need more than what legacy apps can offer
As Pegasystems CTO Don Schuerman says, all of this makes it possible for organizations to adjust the processes for reasons like ensuring that a service level agreement (SLA) is fulfilled.
As organizations pour more money into business transformation initiatives, many are finding out that the batch-oriented legacy apps typically used to process data overnight are not good for powering interactions with customers in real-time.
Schuerman noted that as a result of this, organizations have to modernize applications using platforms like Kafka to enable data streaming between apps and platforms since legacy applications use ineffective methods.
The future of data interaction
The switch from batch to reactive real-time processes is crucial, as Schuerman explains. Support for event streaming will play a big role in enabling organizations to reach this level. Instead of waiting to analyze the data as it rests in the cloud, they can analyze it while it is in transit.
AI is becoming more democratized, meaning that processes it can be applied to exceed the number of data science experts needed to hold organizations’ hands through the technical side. Now, those organizations can benefit too without handling the difficult side of data management.