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TokenAtlas

Case studies

How teams model and reduce their AI costs

Worked scenarios showing how startups, agencies and enterprise teams attribute AI spend, spot overruns and choose cheaper models — built from modelled TokenAtlas calculations.

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Illustrative examples. Every study below is a composite scenario built from modelled TokenAtlas calculations. Companies, figures and quotes are illustrative and do not represent verified customer results.

All case studies

  • Illustrative Example

    NovaStack: 38% lower AI spend in 14 days

    Industry:
    B2B SaaS
    Stage:
    Seed / Series A

    A product team shipping AI features every sprint gains feature-level cost attribution and cuts modelled OpenAI spend by 38%.

    • -38% AI cost
    • 14 days to impact
    • Full visibility
    Read case study: NovaStack: 38% lower AI spend in 14 days
  • Illustrative Example

    PixelForge AI: per-client cost tracking restores margin

    Industry:
    Marketing / AI automation agency
    Stage:
    10–50 active client projects

    An agency maps AI cost to each client project, catches overruns early and protects gross margin on fixed-fee retainers.

    • +22% gross margin
    • Per-client view
    Read case study: PixelForge AI: per-client cost tracking restores margin

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