Redefining Process Optimization: Celonis’s Journey from SaaS to AI-Driven Outcomes

In “Generative AI’s Act o1”, most recent article [1] from Sequoia Capital, the authors note the arrival of “the agentic reasoning era” when research in the Generative AI is shifting from “thinking fast”—rapid-fire pre-trained responses—to “thinking slow”— reasoning at inference time. They argue that this evolution is unlocking a new cohort of agentic applications.

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As a Celonis Value Assessment Expert at Vialto Consulting Ltd. [2] (Celonis being the leading provider of Process Mining SaaS), the interesting part was where they present their views on what this means for the SaaS universe.

Notably, they seem to have changed their minds on SaaS companies’ future. Initially, they thought these companies would be just fine. Now it looks like something just recently thought to be impossible, is becoming a reality - SaaS companies, enterprises with some of the highest customer retention rates worldwide, are at risk of becoming disposable because of AI

To stay in style, I asked Chat GPT o1-preview (a RAG/RAR model?) to start with this Sequoia article, study the landscape and try to reason and apply the scenarios described to the case of Celonis, a marginally AI native company.

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Please read the result below (and the entire Sequoia article [1] and share your thoughts on this topic.

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"The Future of Celonis in the Age of Agentic AI: Navigating the Shift from SaaS to Service-as-a-Software

The advent of agentic reasoning in Generative AI is ushering in a new era where the traditional Software-as-a-Service (SaaS) model is evolving into a "Service-as-a-Software" paradigm. This shift has profound implications for SaaS companies like Celonis, a leader in Process Mining SaaS. Let's explore how the scenarios described by Sequoia Capital could shape Celonis's future.

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From Selling Software to Selling Outcomes

Celonis has built its reputation by providing powerful process mining tools that help organizations visualize and optimize their operational processes. Traditionally, clients subscribe to Celonis's software on a per-seat basis, leveraging the platform to gain insights and drive improvements.

However, the emerging trend highlighted by Sequoia is a move towards AI companies selling work—delivering specific outcomes—rather than just providing software tools. For instance, instead of offering software that helps identify inefficiencies, an AI-driven solution could automatically detect, analyze, and even rectify process bottlenecks, charging clients based on the tangible value or outcomes achieved.

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The Rise of Agentic Applications in Process Mining

Agentic applications are AI systems capable of performing complex tasks with minimal human intervention. In the context of process mining, this could translate to AI agents that autonomously monitor, analyze, and optimize business processes in real-time.

This shift presents both a challenge and an opportunity for Celonis:

• Challenge: New AI-native entrants might offer turnkey solutions that promise immediate results without the need for extensive setup or user expertise. These solutions could appeal to businesses looking for efficiency without the overhead of managing complex software.
• Opportunity: Celonis can leverage its deep domain expertise and vast data repositories to develop advanced AI capabilities that competitors cannot easily replicate. By integrating agentic reasoning, Celonis could enhance its platform to not only identify issues but also recommend and implement solutions autonomously.

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Adapting to the Service-as-a-Software Model

To stay ahead in this evolving landscape, Celonis might consider the following strategies:

1. Transition to Outcome-Based Offerings: Shift from a subscription-based model to an outcome-based model where clients pay for the actual improvements realized. This aligns with the trend of selling work and emphasizes the value delivered.
2. Develop AI-Native Solutions: Invest in AI research and development to create agentic applications within the Celonis platform. This includes building AI agents capable of predictive analytics, autonomous decision-making, and real-time process optimization.
3. Enhance High-Touch Engagements: While AI allows for automation, complex enterprise environments still require trust and personalized solutions. Celonis can strengthen relationships through consultative services that complement its AI offerings.
4. Expand into New Service Areas: Leverage AI to extend beyond process mining into adjacent services such as automated compliance checks, risk management, and operational forecasting.

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Learning from the Past to Inform the Future

Sequoia draws a parallel between the current AI shift and the transition from on-premise software to SaaS two decades ago. Just as many on-premise vendors struggled to adapt to SaaS, today's SaaS companies need to evolve to meet the demands of the AI era.

Celonis can take inspiration from companies that successfully navigated past transitions by:

• Embracing Innovation: Continuously investing in cutting-edge technologies to stay ahead of industry trends.
• Agile Business Models: Being willing to pivot and adapt business models in response to market changes.
• Customer-Centric Approach: Focusing on delivering exceptional value and outcomes for clients to build long-term loyalty.

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Conclusion: Pioneering the Next Phase of Process Optimization

The integration of agentic AI into business services is inevitable and represents a significant shift in how value is delivered. For Celonis, this is an opportunity to pioneer the next phase of process optimization by:

• Transforming its offerings to provide not just insights but also automated, actionable solutions.
• Redefining its value proposition around tangible business outcomes.
• Strengthening its market position by becoming an AI-native leader in process services.

?By proactively adapting to these trends, Celonis can continue to lead in its field and offer unparalleled value to its clients in the age of AI-driven services." (Chat GPT o1-preview)

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1. link to the Sequoia Capital article: https://www.sequoiacap.com/article/generative-ais-act-o1/?utm_source=thetechoasis.beehiiv.com&utm_medium=newsletter&utm_campaign=should-ai-s-kill-openai-s-swarm-the-future-of-ai-training&_bhlid=dc2300e5568561b6489aa949e2b97117b59eeec2

2. https://vialto.hu/process-mining/