Celonis

Overview

Celonis offers an Execution Management System (EMS) that integrates process mining, process intelligence, and automation capabilities to identify and resolve operational inefficiencies within organizations. Founded in 2011, Celonis developed its core technology around process mining, which extracts event data from enterprise systems (such as ERP, CRM, and SCM) to reconstruct and visualize actual process flows. This approach allows businesses to gain an objective understanding of how processes are executed, rather than relying on assumed or documented processes Celonis Process Mining overview.

The platform is designed for large enterprises seeking to optimize complex, cross-functional operations. It applies to various business areas, including supply chain management, financial operations, procurement, and customer service. By analyzing event logs, Celonis can detect deviations from standard processes, identify root causes of bottlenecks, and quantify the impact of inefficiencies. For example, in a procurement process, it might reveal why certain invoices are delayed or why specific vendors are consistently chosen despite higher costs.

Celonis's offerings extend beyond mere analysis to include execution management. This involves providing actionable insights and recommending intelligent automations to improve process performance. The system can trigger alerts, suggest optimal next steps, or integrate with Robotic Process Automation (RPA) tools to automate repetitive tasks or correct process deviations. The company emphasizes a data-driven approach to continuous process improvement, moving organizations toward their "execution capacity" by eliminating friction in operational workflows Celonis Execution Management System.

While the core analytical and process improvement functionalities are accessed through its web interface, Celonis offers a Python SDK and APIs. These are primarily used for data extraction, developing custom connectors to integrate with various source systems, and embedding process insights into other enterprise applications. This developer-centric approach supports extending the platform's reach and customizing its data ingestion capabilities. According to a 2023 report by Gartner, process mining tools like Celonis are increasingly being adopted by organizations to enhance operational resilience and drive digital transformation initiatives Gartner Magic Quadrant for Process Mining Tools. Celonis's focus is on providing a comprehensive solution for process discovery, analysis, and targeted action to drive measurable business outcomes.

Key features

• Process Mining: Automatic discovery, visualization, and analysis of actual business processes from system event data. Identifies bottlenecks, deviations, and inefficiencies.
• Object-Centric Process Mining (OCPM): An evolution of process mining that models processes around business objects (e.g., orders, invoices) and their relationships, providing a more holistic view of complex, interconnected processes Celonis OCPM documentation.
• Process Simulation: Allows users to model and test the impact of proposed process changes or automations before implementation, predicting outcomes and ROI.
• Task Mining: Captures user interaction data from desktops to understand micro-level tasks and identify automation opportunities within individual user workflows.
• Execution Apps: Pre-built or custom applications that embed process intelligence and automation directly into operational workflows, guiding users to take optimal actions.
• Automation Capabilities: Integrates with RPA and other automation tools to automatically address identified inefficiencies and execute recommended actions.
• Analytic Studio: Provides a customizable environment for creating dashboards, reports, and analyses to monitor process performance and track KPIs.
• Data Integration: Connectors to various enterprise systems (e.g., SAP, Oracle, Salesforce) for extracting event data, supporting real-time and batch processing.

Pricing

Celonis offers custom enterprise pricing for its Execution Management System. Details are available upon direct consultation with their sales team.

For specific pricing inquiries and to receive a tailored quote, prospective customers are directed to contact Celonis directly via their pricing page.

Common integrations

• SAP ERP: Direct connectors for extracting process data from SAP ECC and S/4HANA systems Celonis SAP Extractor documentation.
• Salesforce: Integration for analyzing customer service, sales, and marketing processes.
• Oracle ERP: Connectors for various Oracle enterprise applications.
• ServiceNow: Used for optimizing IT service management (ITSM) and other workflow processes.
• UiPath: Integration with UiPath's RPA platform for automating identified process improvements Celonis UiPath Integration Guide.
• Microsoft Dynamics 365: Data extraction and analysis for finance, supply chain, and customer engagement processes.
• Workday: Integration for HR and finance process analysis.
• Custom Data Sources: Via Python SDK and APIs, allows for connecting to virtually any data source with event logs.

Alternatives

• UiPath Process Mining: Offers process discovery, analysis, and monitoring, often integrated with its broader RPA platform.
• SAP Signavio Process Intelligence: Provides process mining, modeling, and management capabilities, integrated within the SAP ecosystem.
• Appian Process Mining: Part of Appian's low-code platform, offering process discovery and optimization with integrated workflow automation.

Getting started

To begin with Celonis, a common first step involves setting up data extraction to feed event logs into the platform. This example demonstrates a conceptual Python snippet using a hypothetical Celonis API client to upload event data. In a real-world scenario, you would use a dedicated Celonis extractor or SDK for your specific source system.

import requests
import json

# This is a conceptual example. Actual Celonis SDK/API usage may vary.
# Replace with your actual Celonis API endpoint and authentication details.
CELONIS_API_BASE_URL = "https://your-celonis-instance.celonis.cloud/api/public/1.0/" # Example URL
API_TOKEN = "YOUR_CELONIS_API_TOKEN"
EVENT_COLLECTION_ID = "YOUR_EVENT_COLLECTION_ID"

headers = {
    "Authorization": f"Bearer {API_TOKEN}",
    "Content-Type": "application/json"
}

def upload_event_data(event_data_list):
    """
    Uploads a list of event data records to Celonis.
    Each event record should contain at least an activity, case_id, and timestamp.
    """
    endpoint = f"data-integration/event-collections/{EVENT_COLLECTION_ID}/events"
    url = f"{CELONIS_API_BASE_URL}{endpoint}"

    payload = {
        "events": event_data_list
    }

    try:
        response = requests.post(url, headers=headers, data=json.dumps(payload))
        response.raise_for_status() # Raise an exception for HTTP errors (4xx or 5xx)
        print(f"Successfully uploaded {len(event_data_list)} events.")
        print(f"Response: {response.json()}")
    except requests.exceptions.HTTPError as http_err:
        print(f"HTTP error occurred: {http_err} - {response.text}")
    except Exception as err:
        print(f"An error occurred: {err}")

if __name__ == "__main__":
    # Example event data (replace with actual data from your systems)
    sample_events = [
        {
            "case_id": "order_123",
            "activity": "Order Created",
            "timestamp": "2026-05-01T10:00:00Z",
            "resource": "User A",
            "event_id": "evt_001"
        },
        {
            "case_id": "order_123",
            "activity": "Payment Received",
            "timestamp": "2026-05-01T10:30:00Z",
            "resource": "System X",
            "event_id": "evt_002"
        },
        {
            "case_id": "order_123",
            "activity": "Items Shipped",
            "timestamp": "2026-05-02T09:00:00Z",
            "resource": "Warehouse Bot",
            "event_id": "evt_003"
        }
    ]

    # In a real application, you would fetch this data from your source systems
    # and format it according to Celonis's event log requirements.
    upload_event_data(sample_events)

After data is uploaded, users typically access the Celonis web interface to configure analyses, build dashboards, and apply process mining algorithms. For detailed developer documentation on specific APIs and SDKs, refer to the official Celonis API Reference.