This Celonis video shows an analyst quickly creating a custom analysis from scratch through a simple conversational interface and without writing a single line of PQL* code.
The user inputs a query or request that describes the desired analysis, and LLM for PQL Generation uses its deep learning algorithms to analyze the input and identify key information, such as the desired fields, tables, and conditions. It then generates PQL code that corresponds to the query or command using standard PQL syntax and conventions.
This is a prime example of using Generative AI in Process Mining!
LLM for PQL Generation reduces the need for manual coding and has the ability to learn from past queries and adapt to new requirements. This allows it to streamline workflows, improve data accuracy and enable faster, more efficient data retrieval.
*The Process Query Language (PQL) is a domain-specific programming language designed to translate business questions into executable process queries and then display the query results. It is an integral part of the Celonis software architecture, and all Celonis applications use it to query data from a data model.
