Celonis vs Modal

Side-by-side comparison of AI visibility scores, market position, and capabilities

Celonis leads in AI visibility (78 vs 45)

Celonis

LeaderInfrastructure

IT Operations

Process mining leader with $13B valuation; AI platform analyzing event logs from SAP and Salesforce to identify bottlenecks and automate process improvements.

AI VisibilityBeta
Overall Score
B78
Category Rank
#1 of 68
AI Consensus
69%
Trend
stable
Per Platform
ChatGPT
85
Perplexity
82
Gemini
85

About

Celonis is the global leader in process intelligence, providing an AI-powered platform that mines event log data from enterprise systems (SAP, Salesforce, Oracle) to visualize, analyze, and optimize business processes in real time. Founded in 2011 in Munich, Germany by Alexander Rinke, Bastian Nominacher, and Martin Klenk, Celonis pioneered the process mining category and has grown it into a major enterprise software segment. The company reached a $13 billion valuation in 2022, making it one of Europe's most valuable software companies.

Full profile

Modal

EmergingAI & Machine Learning

Serverless ML

Serverless GPU cloud platform for AI/ML with Python-native deployment and per-second billing; developer-favorite scaling from zero competing with Replicate and Beam for AI compute.

AI VisibilityBeta
Overall Score
C45
Category Rank
#1 of 1
AI Consensus
55%
Trend
up
Per Platform
ChatGPT
38
Perplexity
50
Gemini
53

About

Modal is a serverless cloud computing platform purpose-built for AI and machine learning workloads — providing on-demand GPU compute that scales instantly from zero with per-second billing, container management, distributed training support, and a Python-native developer experience that makes running ML workloads in the cloud feel as simple as running code locally. Founded in 2021 in New York City and backed by Redpoint Ventures and other investors, Modal has grown rapidly as AI development has accelerated demand for flexible, developer-friendly GPU infrastructure.\n\nModal's developer experience is its primary differentiator — engineers write Python functions decorated with @modal.function() and deploy them to the cloud with a single command, with Modal handling container building, GPU provisioning, auto-scaling, and execution. The platform supports training jobs that need distributed compute across multiple GPUs, model serving endpoints that scale to zero when unused (eliminating idle GPU costs), and batch inference jobs that process large datasets. The per-second billing model means developers pay only for actual compute time, not provisioned instances.\n\nIn 2025, Modal competes in the AI infrastructure market with Replicate, Beam, Banana, and major cloud providers' managed ML services (AWS SageMaker, Google Vertex AI, Azure ML) for serverless GPU compute. The market for AI-specific cloud infrastructure has grown dramatically as the number of ML engineers deploying models to production has expanded — traditional cloud providers require significant DevOps expertise to use GPU instances effectively, while Modal's Python-native approach reduces the barrier to entry. Modal has attracted a strong developer following among AI researchers and ML engineers building production AI applications. The 2025 strategy focuses on growing the developer community, adding enterprise features (dedicated GPU capacity, private networking, compliance), and expanding the hardware options available (H100 GPUs, custom accelerators).

Full profile

AI Visibility Head-to-Head

78
Overall Score
45
#1
Category Rank
#1
69
AI Consensus
55
stable
Trend
up
85
ChatGPT
38
82
Perplexity
50
85
Gemini
53
75
Claude
39
75
Grok
37

Capabilities & Ecosystem

Capabilities

Only Celonis
IT Operations
Only Modal
Serverless ML

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