Organizations are powered by processes. Nowadays, most of the core processes of a company are executed digitally, powered by transactional systems such as ERPs, CRMs, etc. Processes ensure that goods are produced predictably and meet quality standards, they make sure that these are shipped to the customer in time, but also that employees get their monthly paychecks. They are everywhere.
Effective and efficient execution is what makes good companies great. Therefore it is vital to the long-term success of a company to understand, control, and continuously improve its processes. Transactions which document the execution of processes exist inside of the systems running these processes and this data is incredibly valuable for understanding execution today and driving execution tomorrow. To leverage this data in a time- and cost-effective manner, new technologies are required. This is where Celonis Technology is coming in.
Our goal is to make data-driven process execution and enhancement accessible to business users. The technical challenges are manifold. On the backend side, we have large amounts of data to ingest and process, stability and reliability requirements, advanced algorithms, complex infrastructures to integrate with. On the frontend side, we need to provide the user with tools and guidance on how to use all of these powerful functionalities in an efficient and natural way. All of that while continuously working on scalability and cost-effectiveness of the platform to keep up with our growth.
We are building technology because we believe that execution management is a problem and a market big enough to justify the investment. What we can deliver with bespoke technologies when compared with off-the-shelf are:
More value due to more depth<!— htmlmin:ignore —>
Faster time to value due to better tool support and optimized user experiences<!— htmlmin:ignore —>
Cost advantages due to better hardware efficiency<!— htmlmin:ignore —>
Network effects which are not possible with off-the-shelf technologies due to semantic understanding of the data and workloads we are managing.<!— htmlmin:ignore —>
To build a system which allows for ingesting data and turning it into a process-oriented meta model, querying this model, visualizing and collaborating on it, and leveraging it for driving automation requires a broad set of technologies and expertise. Over the years, we have built
A multi-tenant platform with governance features built-in, including a multi-tenant ORM<!— htmlmin:ignore —>
A fully-fledged data extraction and integration stack for moving data into our system<!— htmlmin:ignore —>
A process database called SaolaDB, hosting and running queries on large process models including an optimized query engine and language, PQL<!— htmlmin:ignore —>
A content and package management system including version control and a CLI<!— htmlmin:ignore —>
Lots of visualization and UI components<!— htmlmin:ignore —>
Charting frameworks<!— htmlmin:ignore —>
A reusable UI toolkit<!— htmlmin:ignore —>
… and much more<!— htmlmin:ignore —>
Last but not least we have built a product portfolio making use of all of these capabilities.
While we are a heavy user of open source and off-the-shelf services, we believe that for the differentiated parts of our product, we need to support them with carefully crafted in-house developed technologies.