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AI / SaaS

From a stalled machine-learning prototype to a production SaaS

An AI startup had a genuinely strong model and nothing around it — no API, no infrastructure, no monitoring, and investors who wanted traction within six months. We built the product that turned the model into a business.

ClientAI startup (confidential)
IndustryAI / SaaS
What we deliveredProduct engineering, ML operations, cloud platform, billing
From a stalled machine-learning prototype to a production SaaS
API-firstModel exposed as a product
18 monthsPrototype to seven-figure MRR
Series ARaised on the platform's traction

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

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