Revenue scales with workflow adoption

This pricing model makes Artemis behave less like a standard research seat sale and more like a data system that spreads across an investment team’s daily work. A junior analyst might start in the terminal or Sheets, but the account gets much larger once the same team plugs Artemis into dashboards, internal models, APIs, and Snowflake pipelines. That turns expansion into workflow adoption, because more research steps start running on Artemis data instead of separate tools.

• The packaging shows that lower tiers are metered by usage, not just by named users. Artemis pricing includes call limits on free plans and larger workflow features on paid plans, while institutional products add API, data share, and broader access. That means a customer can outgrow a plan by running more analysis, even if headcount stays flat.
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• This is the same pattern used by infrastructure flavored data companies. Token Terminal sells a web product for analysts and separate custom access for teams that want data inside their own models and systems. In practice, the more a fund automates screening, portfolio monitoring, and memo building, the more valuable direct data access becomes.
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• It also fits Artemis’s product direction. Artemis has moved from a crypto metrics terminal toward a research workflow that combines dashboards, comparable data, and AI assisted thesis building across tokens, equities, and private companies. A platform trying to sit inside research creation naturally monetizes depth of use better than simple seat count.
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Going forward, the biggest accounts should come from teams that make Artemis part of their core research stack. If Artemis becomes the place where investors pull data, build models, compare assets, and feed internal systems, revenue can keep rising through deeper integration long before a firm needs many more seats.