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Select companies in the slots below to reveal a useful side-by-side view. You can compare up to four companies and change any selection later.
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| Description | ||||
| Summary | AI-ready data and analytics automation platform for data preparation, self-service analytics, forecasting, simulation and operationalized insights. | |||
| Description | Alteryx One unifies data preparation, blending, analytics, generative AI, predictive modeling, workflow automation, governance, collaboration, and deployment flexibility across cloud, on-prem, and hybrid environments. It helps business users, analysts, data scientists, and IT teams build reusable governed workflows, prepare AI-ready data, automate recurring reporting and analytics tasks, and operationalize insights through apps, reports, APIs, and integrations. | |||
| Positioning | AI-ready data and analytics platform / Alteryx One | |||
| Key facts | ||||
| HQ location | Irvine, CA, USA | |||
| Founded | 1997 | |||
| Employee range | 1001-5000 | |||
| Funding stage | Acquired | |||
| Company type | Unknown | |||
| Pricing model | custom quote, subscription | |||
| Last updated | Jun 21, 2026 | |||
| Financials | ||||
| Revenue estimate | Last public FY2023 revenue $970M; post-take-private revenue undisclosed | |||
| Valuation estimate | $4.4B transaction value incl. debt (Dec 2023 / Mar 2024 take-private) | |||
| Investments | $4.4B take-private acquisition by Clearlake Capital and Insight Partners (closed Mar 2024); prior venture backing included Insight, ICONIQ, Sapphire/SAP Ventures, Toba, Meritech | |||
| Relationships | ||||
| Target customers | Enterprise analytics teams, business analysts, data teams, finance, IT, sales & marketing, supply chain | |||
| Key competitors | Tableau, Microsoft Power BI, Dataiku, KNIME, Databricks, Qlik, ThoughtSpot | |||
| Known customers | Bank of America, Coca-Cola, Siemens Energy, MUFG Bank, McLaren Racing | |||
| Segments & Industries | ||||
| Segments | AI Workflows, AI Agents, AI Developer Tools, Knowledge & RAG, Document AI, LLM Deployment, AI Quality & Observability, Traditional ML, AI Governance & Risk, Analytics & BI | |||
