Production-Grade AI Integration

THE SITUATION

A global FMCG company operating across multiple international markets needed to integrate AI capabilities into its existing digital product ecosystem. The requirement was production-grade implementation under tight delivery timelines - not a proof of concept or a pilot, but a system that needed to function at scale from the point of deployment.

The core challenge was integration fidelity: ensuring the AI components behaved predictably within an existing product architecture, scaled reliably under operational load, and did not introduce systemic risk to products already in market. The client name is withheld under NDA.

WHAT KONTORVA DELIVERED

Kontorva delivered end-to-end AI system integration across the client's product stack. Our approach began with a thorough assessment of the existing architecture before any AI components were introduced - establishing integration points that would maintain system stability rather than accelerate risk.

We prioritised scalability and product alignment over feature velocity: the AI components were designed to operate consistently across the client's international deployment environments, not optimised for a single market configuration. Delivery was structured to reduce execution risk at each integration milestone, with clear handover criteria at each stage.

TECHNOLOGIES

AI/ML system integration · Production-grade deployment architecture · Cross-market scalability engineering · Data pipeline integration · Digital product ecosystem engineering

OUTCOME