01 The challenge
The prototype worked in a notebook and a demo, and nowhere else. It could not serve more than one user, had no way to be integrated by customers, and the founders had no engineering capacity to build the platform themselves. Every month without a sellable product ate into runway.
02 What we did
- Productisation of the model: versioned inference service, batch and real-time APIs, SDKs and documentation
- Multi-tenant SaaS platform with onboarding, workspaces, usage metering and self-service billing
- MLOps — training pipelines, evaluation, drift monitoring and safe model rollouts
- Scalable cloud infrastructure with security and data-isolation controls enterprise buyers expect
- Analytics giving the founders the traction metrics investors asked for
03 The results
- Revenue grew from zero to seven-figure monthly recurring revenue within eighteen months
- Hundreds of paying customers on a self-service platform
- Series A raised on the back of the traction
- An enterprise-ready platform the startup's own team now runs