Plotly
Plotly is a code-first data app and visualisation platform with open source and enterprise SaaS.
Plotly operates in the Unclassified segment.
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- Founded
- 2012
- Headquarters
- 5555 Avenue de Gaspé #118 Montréal, QC H2T 2A3, CA
- Core Segment
- Unclassified
- Company Size
- 50–200
- Official Links
- Website
- Verified
- 2026-03-12
Key insights about Plotly
Subsidiaries
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Competitors
Key competitors include Tableau, Qlik.
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Acquisitions
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Plotly: About
The company follows an open-core, code-centric analytics model. It maintains popular open-source graphing libraries and a Python framework for analytical web applications, which act as adoption and developer acquisition channels. On top of this open foundation, it offers commercial platforms: an AI-native desktop tool to generate analytical apps, a hosted cloud service for publishing and collaborating on those apps, and an enterprise platform for secure, large-scale deployment and governance. Value is created by enabling technical and semi-technical teams to build custom, interactive data applications using familiar programming languages instead of proprietary BI stacks, and by simplifying deployment, security and operations for those apps. Revenue comes from paid cloud plans, enterprise licences and support, and related services, while grants and strategic investments help fund development of the open-source ecosystem.
Plotly: Market Position
Plotly is a Canadian software company that develops open-source and commercial tools for building interactive data visualisation and analytics applications, primarily in Python and JavaScript. Its core technologies include a JavaScript charting library, open-source Python frameworks for analytical web apps, and enterprise platforms for deploying and managing those apps, increasingly extended with AI-assisted app creation.
The company monetises through SaaS subscriptions for hosted analytics and AI-assisted app creation, as well as enterprise licences and managed deployments for its production app platform. Customers are mainly data science, analytics and engineering teams in organisations that need to build and operate custom, code-based analytical applications, rather than using traditional business intelligence tools. Open-source libraries drive adoption, while commercial cloud and enterprise products capture paying users.
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