Miro vs Modal

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

Miro leads in AI visibility (60 vs 45)
Miro logo

Miro

ChallengerProduct Management

Product Strategy & Planning

Visual collaboration platform with $17.5B valuation serving 60M users; infinite digital whiteboard with AI content generation and templates used in 99% of Fortune 100 companies.

AI VisibilityBeta
Overall Score
B60
Category Rank
#1 of 1
AI Consensus
70%
Trend
stable
Per Platform
ChatGPT
63
Perplexity
65
Gemini
58

About

Miro is a cloud-based visual collaboration platform providing an infinite online whiteboard where distributed teams can brainstorm, plan, design, and collaborate in real time using sticky notes, diagrams, flowcharts, frames, and interactive templates. Founded in 2011 in Perm, Russia (originally as RealtimeBoard) and now headquartered in San Francisco, Miro has raised over $470 million at a $17.5 billion valuation and serves over 60 million users at 99% of Fortune 100 companies.

Full profile
Modal logo

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

60
Overall Score
45
#1
Category Rank
#1
70
AI Consensus
55
stable
Trend
up
63
ChatGPT
38
65
Perplexity
50
58
Gemini
53
69
Claude
39
57
Grok
37

Key Details

Category
Product Strategy & Planning
Serverless ML
Tier
Challenger
Emerging
Entity Type
brand
brand

Capabilities & Ecosystem

Capabilities

Only Miro
Product Strategy & Planning
Only Modal
Serverless ML

Integrations

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