Millwright Book a call
Industry

Data platforms for SaaS companies

SaaS companies live and die by a few numbers: recurring revenue, churn, expansion, and the cost to serve each customer. I have run production ML pipelines for a SaaS venture and built subscription analytics for a direct-to-consumer business.

What is different about SaaS data

SaaS metrics look simple and are not. Churn has several reasonable definitions, recurring revenue depends on how you treat discounts and pauses, and product usage lives in a different system from billing. When each team picks its own definition, the board deck and the finance model stop agreeing, and nobody notices until a fundraise or an acquisition puts both on the same table.

Where I help

  • Metrics defined once. A semantic layer for recurring revenue, churn, and retention, so product, finance, and the board read the same numbers.
  • Pipelines that stay up. Orchestrated pipelines with CI/CD, monitoring, and alerting, built for the uptime a customer-facing product needs.
  • Models that ship like code. Feature pipelines, scheduled scoring, and CI gates, so models move from notebooks into production.
  • Cost per customer. Unit economics for the data platform itself, so spend grows with revenue rather than ahead of it.

Related

  • Close-up of a dark circuit board with gold contacts
    Case study
    99.8%

    Keeping ML training pipelines at 99.8% uptime

    A semiconductor manufacturer's SaaS MLOps venture needed pipelines that customers could count on. They ran at 99.8% uptime while volumes grew across fabs.

    Read it
  • Three amber supplement bottles on a light surface
    Case study
    $425M

    The data foundation behind a $425M acquisition

    A fast-growing subscription health business needed governed data under HIPAA, PCI DSS, and SOX. The foundation supported its growth analytics and a $425M acquisition.

    Read it
  • A pencil and a scale ruler resting on a technical drawing
    Service

    Build

    You know what you need and want it built properly. Designed, built with your engineers, documented, and running in your accounts.

    Read it
  • A leather notebook, a spiral notepad, and a pen on a concrete desk
    Service

    Head of Data

    You need a data platform leader before you are ready to hire one. Roadmap, hiring plan, and metrics, then a clean handoff.

    Read it

Working in SaaS?

Bring the number that moved or the bill that grew. You will leave the call with a first read and a straight answer on whether I can help.

Book a call