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The strategic partnership has developed collective products to help customers map operations across people, processes, and systems.

Celonis is forming a tactical partnership with US-based ServiceNow. The duo aims to assist customers in recognizing workplace operations that have the potential for automation.

The collaboration began when ServiceNow made an undetermined investment in Celonis. The partnership’s ultimate goal is to amalgamate ServiceNow’s workflow platform with Celonis’ execution management system, which is widely known for analyzing data to solve problems and introducing automated decision-making.

What is ServiceNow?

ServiceNow is an American software company based in Santa Clara, California. The firm is widely known for developing cloud computing platforms to assist companies in managing workflow operations. ServiceNow targets enterprises by creating digital workflows to improve employee and customer experience and boost productivity.

What is Celonis?

Celonis, ServiceNow’s competition, has its origination in Germany. As a result, the business software firm has earned the reputation of being Germany’s most prized startup. Celonis raised $1 billion in funds in June. Now, Celonis is valued at more than $11 billion.

What the collaboration will bring

The alliance between the two software giants can transform the digital ecosystem. While ServiceNow presents its advanced Execution Management System, Celonis offers its streamlined workflow optimization processes to refine business processes.

The partnership will work around merging ServiceNow’s low-code workflow platform and real-time processes with Celonis’ process refinement and execution tools. This way, the companies can assist customers in mapping workflow operations, covering employees, customers, processes, and systems.  As reported by the firms, the combined technology will be released in the first half of 2022.

This collaboration is predicted to produce fruitful results. The resulting products can help their clients use their heaps of collected data to improve execution.